Skip to main content
PLOS ONE logoLink to PLOS ONE
. 2024 Jun 28;19(6):e0305959. doi: 10.1371/journal.pone.0305959

The racialization of pit bulls: What dogs can teach us about racial politics

Michael Tesler 1,*, Mary McThomas 1
Editor: Hans H Tung2
PMCID: PMC11213322  PMID: 38941314

Abstract

Many have argued that discrimination against pit bulls is rooted in the breed’s association with Black owners and culture. We theoretically and empirically interrogate that argument in a variety of ways and uncover striking similarities between the racialization of pit bulls and other racialized issues (e.g., poverty and crime) in public opinion and policy implementation. After detailing the reasons to expect pit bulls to be racialized as Black despite dog ownership in the U.S. generally being raced as white, the article shows: (1) Most Americans associate pit bulls with Black people. (2) Anti-Black attitudes, in general, are significant, independent, predictors of both anti-pit views and of preferring other breeds over them; (3) stereotypes of Black men as violent, in particular, are significant, independent, predictors of both anti-pit views and of preferring other breeds over them. (4) Implicit racialization through a national survey experiment further eroded support for legalizing pits, with the treatment effect significantly conditioned by respondent’s race. And (5) state-level racial prejudice is a significant negative predictor of enacting legislation to preempt breed-specific bans. We conclude with our findings’ broader insights into the nature of U.S. racial politics. Michael Tesler, mtesler@uci.edu, corresponding author, is Professor of Political Science at UC Irvine; Mary McThomas, mary.mcthomas@uci.edu, is Associate Professor of Political Science at UC Irvine. An earlier version of this paper was presented at the American Political Science Association’s annual meeting. We thank Maneesh Arora, Rachel Bernhard, Nathan Chan, Louis Pickett, David Sears, DeSipio, Adam Duberstein, Jane Junn, Claire Kim, Jessica Manforti, J. Scott Matthews, Justin.

Introduction

Separately, the young Black man and the pit bull make people cross to the other side of the street; together, they are a picture of unmitigated threat.”

-Claire Jean Kim, Dangerous Crossings. pg. 272. [1]

Racialization occurs when an issue, person, policy, or even a specific dog breed becomes infused with racial connotations [2]. Crime and poverty, for example, are thought to be racialized via their connections to African American perpetrators and welfare recipients [26]. In both instances there is an empirical link between race and the issue, as African Americans are disproportionately more likely to be incarcerated and receive welfare than white people. But those associations are then framed in an especially negative light by the news media, which in turn helps erode racially prejudiced whites’ support for welfare and compassionate criminal justice policies. The implementation of these racialized policies across the states then reflects their underlying racialization, as the most racially prejudiced states have less generous welfare benefits and more punitive crime policies (see discussion below).

Many have suggested that pit bulls are similarly racialized. Several scholars and journalists have even argued that the widespread and well-documented societal prejudice and discrimination against pit bulls [7,8] is at least partially rooted in the dog breed’s association with Black men and African American culture. A 2016 op-ed in the Washington Post, for example, contended that breed-specific legislation (BSL) banning pit bulls are likely “proxies by which uneasy majorities can register their suspicions about the race, class and ethnicity of the people who own those dogs” [9]. Katja Guenther [10, pg 155–156] similarly states, “pit bulls are now ‘raced Black,’ and, like Black men, they are consequently subjected to discriminatory policies and practices based on fear of the risk they purportedly pose to whites, to public safety, and to the social order.” After documenting the racialization of pit bulls, Claire Kim [1, pg 273] concludes, “Pit bulls are dying for being Black.” And Bénédicte Boisseron [11, pg. 152] argues in her book, Afro-Dog, “When one becomes aware of the racialization of the pit bull through putative black ownership, pit bull bans across America take on the appearance of a modern version of the plantation-era ban [on Black people owning canines].”

Those arguments are compelling and plausible. After all, the pages that follow detail the long line of academic research showing that the news media, the white public, and politicians are often less sympathetic to issues and policies after they’re racialized via negative associations with African Americans. But there have been few quantitative analyses of how race and racial attitudes affect public opinion and public policy toward pit bulls. Moreover, Thompson, Pickett, and Intravia’s [12] recent empirical study found that neither experimentally linking pit bull owners with African Americans via racial imagery, nor harboring stereotypes of pit bull owners as disproportionately Black, were associated with support for banning the breed among college students.

Thompson et al., however, conclude that study by noting the need to replicate their findings with representative samples. They specifically discuss how the young age of their college sample could affect the results if attitudes toward pit bulls have improved since Michael Vick’s 2007 dog-fighting controversy. This is a particularly prescient point. Consistent with the unusually low levels of support for breed-specific bans in Thompson et al.’s data (1.74 on a 1–5 scale), we note multiple times throughout the manuscript that age is one of the strongest predictors of public opinion about pit bulls presumably because American youths have been socialized amidst increasingly positive images of the breed on social media. Younger and college-educated Americans score significantly lower in racial prejudice (see discussion below), as well, which could help further explain why the link between pit bulls and African Americans did not increase support for breed-specific legislation among college students.

So, there are still lots of unanswered questions about the racialization of pit bulls. Does the public, for example, really associate pit bulls with African Americans? If so, has that association eroded support for these dogs, especially among racially prejudiced whites? And are racial prejudice and the politics of race linked to legislation banning these dogs from certain neighborhoods? This article explains the causes and consequences of racializing pit bulls by providing detailed empirical answers to these questions. In doing so, we reveal some striking similarities between the racial politics surrounding pit bulls and the racialization of ostensibly non-racial issues, such as poverty and crime, in both public opinion and in policy implementation across the states. Our analyses of pit bulls, in fact, offer some broader insights into the nature of racial politics in the United States that we discuss in the conclusion.

The racialization of dog ownership and pit bulls

Dog ownership has historically been racialized as white in American society [11,13]. The top panel of Fig 1 shows the modern-day manifestation of that racialization—the large racial divide between Black and white Americans in dog ownership. Whites were roughly twice as likely to own a dog as African Americans were in both a 2005 Pew Poll and in the 2008 National Annenberg Election Survey, with less than one-quarter of African Americans having a pet dog in both surveys. It’s hardly surprising, then, that white people interacted more frequently with dogs and rated them more favorably than African Americans did in six combined national surveys (pooled N > 6,000) we fielded from November 2018 to August 2021 through Lucid—a relatively new opt-in online polling firm whose demographics and experimental treatment effects track well with findings from U.S. probability samples [14,15].

Fig 1. The racial divide over dogs and pit bulls.

Fig 1

Sources: 2008 National Annenberg Election Survey; Pew Social Trends Poll, Oct-Nov 2005; Pooled Lucid Surveys, 2018–2021.

The racial dog-divide is rooted in a variety of factors, including socioeconomic inequality between the races [16] and the legacy of plantation-era laws banning Black people from owning canines [11]. Since respondents who had a pet dog during childhood were nearly twice as likely in our Lucid surveys to own a dog in adulthood as those who didn’t (57% to 30% respectively), the effects of these antebellum restrictions have likely been passed down from generation to generation. Perhaps an even bigger factor, though, is “the recurrent history, on both sides of the Atlantic, of canine weaponry used against the oppressed.” [11, pg. 153].” From Bloodhounds tracking and attacking fugitive slaves, to German Shepherds mauling civil rights protestors in the 1960s, to the Ferguson Police Department’s more recent practice “of deploying canines to bite individuals when the articulated facts do not justify this significant use of force” [17] white authorities have used dogs to terrorize and control Black people.

Despite that history, however, the bottom panel of Fig 1 shows that African Americans are more likely than white people to regularly interact with pit bulls—a modest but highly significant six percentage-point difference. You can see in the display that African Americans are also significantly more likely than whites to say pits are their favorite breed and less likely to rate the breed as their least favorite type of dog. There were not significant differences between the races in how favorably they rated pit bulls; but after controlling for the fact that white people have more favorable views about dogs than Black people do, and that attitudes about dogs in general strongly predict attitudes towards pit bulls (see Table 1), African Americans were significantly more likely than whites to rate pit bulls very favorably (40% to 32% respectively, p < .001).

Table 1. (OLS) predictors of white Americans opinions of pit bulls and other dog breeds.

Net-Fav
Pit Bulls
Net-Fav
9-Dog Scale
Difference: Pit minus Dog Scale Net-Fav
Pit Bulls
Net-Fav
9-Dog Scale
Difference: Pit minus Dog Scale
Blacks Favorability .371*** .184*** .180***
(.049) (.019) (.046)
Whites Favorability -.026 .078*** -.103*
(.056) (.023) (.051)
Dogs Favorability 1.08*** 1.12*** -.043 1.26*** 1.19*** .076
(.057) (.022) (.054) (.129) (.054) (.118)
Party Identification -.024 .013 -.039 -.016 .013 -.029
(.034) (.013) (.032) (.079) (.033) (.072)
Actual Age -.016*** .001*** -.017*** -.010*** .002* -.012***
(.001) (.000) (.001) (.002) (.001) (.002)
Education -.066 -.076*** .008 -.136 -.076 -.060
(.051) (.020) (.048) (.108) (.045) (.099)
Male .049 .012 .038 -.176** -.069* -.106
(.026) (.010) (.023) (.064) (.027) (.058)
Violent: Black Men -.507** -.086 -.421**
(.173) (.072) (.158)
Violent: Black-Wom .119 .032 .087
(.179) (.075) (.163)
Violent: White Men .127 .041 .086
(.159) (.066) (.145)
Violent: White-Wom .294 -.092 .387*
(.179) (.075) (.163)
Violent: Muslim Men -.002 .058 -.060
(.156) (.065) (.143)
Violent:Muslim-Wom .213 .088 .124
(.174) (.073) (.159)
Constant -.161* -.543*** .383*** -.213 -.410*** .197
(.076) (.030) (.071) (.167) (.070) (.153)
R2 .166 .407 .119 .170 .389 .125
Observations 4545 4536 4535 860 860 860

Significance codes:

*p < .05,

**p < .01,

***p < .001.

Note: Dependent variables range from -1 (rate unfavorably) to 1 (rate favorably). All explanatory variables except actual age are coded from 0 to 1, with 1 representing the highest or most conservative. value. Source: Pooled Lucid Surveys 2018–2021; Lucid Survey, August 2021 (Right-hand columns); white respondents only.

Pit bulls gained popularity in African American communities during the late twentieth century as protectors who “afforded security and status to men who feared violence from police and peers” [10, pg 154; see also 1, 1820]. That link was further solidified by the pit bull’s racialized place in media and popular culture. Bronwen Dickey [18, pg 220], for example, describes pit bulls as hip hop’s “unofficial mascot,” with several of the genre’s biggest stars owning and/or appearing in music videos with the breed. And negative associations between pit bulls and African Americans have been reinforced by media and pop-culture portraits of African Americans’ involvement in illegal dogfighting operations [1,10,19].

The upshot is that the public predominantly thinks of pit bulls as a Black-owned dog breed—much the way that they disproportionately associate welfare and violent crime with African Americans [3,21]. In three of our Lucid surveys, which were fielded in June 2020, July 2020, and August 2021, we asked our respondents, “If you had to guess, do you think that white people or black people are more likely to own the following dogs?” Fig 2 shows that white people are perceived as much more likely to own such popular dog breeds as Golden Retrievers, Collies, Labradors, and Dalmatians, which is again consistent with the idea of dog ownership being generally raced as white. But most of our respondents thought African Americans are more likely than whites to own pit bulls and Rottweilers.

Fig 2. Perceptions of whether black or white people are more likely to own certain dog breeds.

Fig 2

Note: Question asked respondents: “If you had to guess, do you think Black people or white people are more likely to own the following dogs?” Source: Pooled Lucid Surveys, June-July 2020, August 2021.

It’s hardly a coincidence, either, that the two dog breeds stereotyped as Black-owned are the two breeds that evoke the most fear from the public. Over 40 percent of respondents in a 2018 Lucid survey we conducted, for example, said that “scary” described pit bulls and rottweilers “extremely” or “very well” (46 and 41 percent, respectively). But only about 10 percent said the same thing about golden retrievers, collies, Dalmatians and Labradors. These four breeds were all rated at least 15 percentage points more favorably than rottweilers and pit bulls in our surveys as well [22]. To be sure, there are plenty of other reasons why people may find these dogs scary, such as their large muscular builds, history of being bred for fighting purposes, and rare but sensationalized involvement in fatal attacks. Yet, the theoretical background and empirical evidence provided in the following sections indicate the breed’s associations with African Americans has played an important and independent part in prejudice and discrimination against pit bulls.

Theoretical background and empirical expectations

A large body of research explains the causes and consequence of racialization in American politics. This process of racialization, whereby certain issues, policies, and people are inextricably associated with specific racial groups, occurs in a variety of ways. Some issues like affirmative action and reparations for African Americans automatically evoke race because there’s such a clear link between the policy and the groups who benefit from them [23]. Barack Obama’s “embodiment of race” as the country’s first African American president made it similarly easy to project hopes and fears about race onto his presidency [24,25]. So much so, in fact, that issues like health care were racialized simply through their connection to his presidency [2527]. Most importantly for our purposes, this “spillover of racialization,” extended all the way into feelings about the Obamas’ dog, Bo [25].

The media often plays a critical role in the racialization process as well. Prior research suggests that the racialization of issues stems in large part from mass communications, which strengthen their association with specific racial groups [2,3,28]. Those associations usually begin with some empirical basis, such as higher incarceration rates among African Americans or white Americans disproportionately dying of opioid overdoses. But the news media often frames those issues differently depending on whether they have a Black or white face attached to them. Many astute analysts, for example, have documented how different the media’s sympathetic coverage of rural white opioid users has been from their negative stories about the crack epidemic in Black communities during the 1980s [2933]. As Raychaudhuri, Mendelberg, and McDonough [34, pg. 168] conclude, “drugs associated with racial minorities are framed with negatively-valenced topics such as crime, while drugs associated with Whites are characterized with positively-valenced topics such as community and family.”

Those different portraits of Black drug use fit well with prior social science research on race, media, and attribution error [3,3537]. The upshot of those cognitive biases is that when white Americans struggle, their troubles are usually attributed to situational forces like overprescribed painkillers. But when non-whites struggle, their plight is more often attributed to negative dispositional traits, such as the group’s supposed poor work ethic and lax moral values. Martin Gilens [3], for instance, famously found that images of Black poverty in newsmagazines reinforced negative racial stereotypes of African Americans as “the underserving poor,” while impoverished whites were portrayed more favorably as victims of economic conditions beyond their control. The news media tends to portray Black criminality more menacingly, too, with Robert Entman and Andrew Rojecki [38, pg. 82] finding “a tendency for Blacks accused of crimes to be portrayed as individuals less than whites—that is, to be lumped together without distinct identities and laden with negative associations.”

We suspect that the media might also portray pit bulls especially unfavorably when they are linked up with African Americans. Qualitative research certainly suggests that they do. We noted earlier, for example, that scholars have documented the ways in which negative associations between pit bulls and Black Americans are propagated by media and pop-culture portraits of African Americans’ involvement in illegal dogfighting operations [1,10,19]. Dickey similarly chronicles the “dark-skinned” imagery and racial fears that were so prominent in the late twentieth century news coverage of “the pit bull panic” [18]. And our subsequent research provides some suggestive quantitative evidence on the heightened negativity of news stories about pit bulls when they’re associated with African Americans [39]. Drawing on automated sentiment analyses from Gary King’s analytics platform, Crimson Hexagon, we found that the net sentiment (positive minus negative) of headline news stories about pit bulls, which explicitly mentioned African Americans, was significantly lower (p < .001) than the already high levels of negativity in all news coverage of the breed (-68 to -48 respectively).

Those negative associations between African Americans and pit bulls in media and popular culture could certainly affect public opinion. Indeed, a large volume of political science research shows that racialized news coverage can heighten the association between racial attitudes and white Americans’ policy preferences [40,41]. The emergence of news coverage linking welfare benefits with “undeserving Blacks” in the 1960s and 1970s eroded support for this policy, especially among racially prejudiced whites [2,3,6,42]. Meanwhile, news coverage connecting Social Security to hardworking white recipients who are getting their just rewards helped make this policy popular, especially among ethnocentric whites who rate their own group higher than racial and ethnic minorities [2,43]. Social scientists have similarly argued that media coverage, which exaggerates Black violence, have helped make racially resentful whites’ more supportive of the death penalty and other punitive criminal justice policies [4446]. Chiricos et al. [21] relatedly found that white Americans significantly overestimated the share of violent crime committed by African Americans and that those misperceptions were linked to support for harsher criminal justice penalties.

Based on those studies, our first formal hypothesis, H1, posits that anti-Black attitudes are a significant, independent, predictor of negative opinions about pit bulls. Relatedly, we also expect that racial prejudice will be more strongly associated with public opinion about pit bulls than it is with other dog breeds. Or, stated more formally, H2 expects anti-Black attitudes to significantly predict rating pit bulls less favorably than other dog breeds.

Issues like welfare and crime aren’t just racialized, though. They also evoke intersectional stereotypes of African American women and Black men respectively [47]. Derogatory portraits of Black women as promiscuous and irresponsible “welfare queens,” for example, have long been weaponized against anti-poverty policies. So, it’s not surprising that there’s an especially strong empirical link between opposition to welfare and stereotypes of Black women as sexually irresponsible [6,48]. Nor is it surprising that widespread societal stereotypes of Black men as violent factor heavily into perceptions of crime and public opinion about the criminal justice system. [45,47,49,50].

These same exaggerated fears of Black men might also be implicated in opposition to pit bulls. After all, Guenther [10, pg 154–55] describes pit bulls as “synonymous with Black masculinity,” stating, “This link between Black masculinity and pit bulls was and still is captured and reinforced through the image of pit bulls as companions to Black male ‘thugs’ depicted in hip-hop and rap media and in the mainstream media, and of pit bulls as part of illegal dogfighting operations involving Black men in both poor urban neighborhoods and the rural south.” Our next formal hypothesis, therefore, is that stereotypes of Black men as violent will be a significant independent predictor rating pit bulls unfavorably even after controlling for stereotypes of Black women and other groups as violent (H3).

As important as observational studies have been in showing how racialized media coverage can affect public opinion, social science experiments provide even stronger evidence. Several experiments, which randomly assigned subjects to receive implicit racialized messages (e.g., racial images and/or race-coded language that does not explicitly reference a particular racial group) about specific issues, have affected white Americans’ opinion about crime, welfare, drug treatment, gun control, government spending, education programs, Social Security, the minimum wage, the Iraq War, and the coronavirus pandemic [2,3,34,43,45,5155]. Based on those studies, H4 posits that implicitly linking pit bulls with African Americans will significantly increase white Americans’ support for banning the breed.

Finally, the racialization of issues like poverty and crime often has important policy consequences. For, as Beth Reingold and Adriene Smith [56, pg. 131] surmised, “State lawmakers have responded to or internalized the racial stereotypes, resentments, and fears that shape judgments of welfare recipients and drive the call for less generous, get-tough welfare policy among whites.” In keeping with that contention, states that score higher in measures of white racial prejudice were less likely to expand Medicaid coverage under the Affordable Care Act and have fewer social welfare benefits, on average, than states whose citizens have more progressive views about race [5759]. States with large Black populations were also less likely to expand Medicaid and have more rigid rules and regulations governing eligibility and work requirements for welfare benefits [6,6062]. Likewise, states with larger Black populations and more racially prejudiced constituents tend to have more punitive criminal justice policies than other states [6366]. Our final hypothesis, then, is that states that score high in racial prejudice will be significantly less likely to enact legislation preempting municipal pit bull bans (H5).

Data and methods

This article employs a wide variety of data, measures, and statistical analyses to formally interrogate those hypotheses. To test the suspected association between white racial prejudice and public opinion about pit bulls formally posited in hypotheses H1-H3 we commissioned seven national surveys from 2018 to 2021, each of which sampled at least 1,000 Americans. As we mentioned earlier, six of the surveys were fielded through Lucid between November 2018 and August 2021 (IRB Exempt Approval HS#2017–3811; see page 3 of the appendix for the informed consent message at the beginning of each survey). While the firm’s demographics and experimental treatment effects track well with findings from U.S. probability samples [14,15], Lucid is a relatively new online survey platform. So, we also replicated our findings with data from a more established polling firm, YouGov, sampling 1,000 respondents as part our team’s module in the 2018 Cooperative Congressional Election Survey (CCES).

The CCES and Lucid surveys both contained the same four questions about pit bulls that previously appeared in a July 2014 YouGov/HuffPost Poll [67]. Those questions asked: (1) if it should be legal or illegal to own a pit bull; (2) if pit bulls are naturally more aggressive than other breeds; (3) if it is safe or too dangerous for pit bulls to live in residential neighborhoods (asked in two of the six Lucid surveys); and (4) if the respondent would personally consider adopting a pit bull. In addition to testing the association between racial attitudes and those four dependent variables, all six of our Lucid surveys asked how favorably respondents rated many of the most popular dog breeds—pit bulls, Labradors, Golden Retrievers, German Shepherds, Collies, Huskies, Bulldogs, Dalmatians, Chihuahuas as well as dogs in general (these dog favorability questions were not included in our CCES team survey). Those items are then used to test H2’s expectation that anti-Black attitudes are significant predictors of rating pit bulls less favorably than other dog breeds.

The Lucid and CCES surveys also contained two blatant measures of racial prejudice. The first measure uses five-category favorable/unfavorable ratings of African Americans. The second measure is a two-item scale of old-fashioned racism (OFR), which taps into aversion to interracial intimacy and has been validated in prior research [68]. These two items asked respondent how strongly they agreed or disagreed with the following statements (1) “I prefer that my close relatives marry spouses of their same race,” (2) “I think it’s alright for Blacks and whites to date each other.” Finally, we included a question about how well the term “violent” described various racial/gender groups to test H3’s contention that exaggerated stereotypes of Black men as violent are significant predictors of negative opinions about pit bulls.

We chose these measures of racial prejudice for a couple of reasons. Most importantly, anti-Black affect, OFR, and anti-Black stereotypes are all only weakly associated with other sociopolitical attitudes [25,69,70], thereby minimizing the risks of spurious correlations with anti-pit attitudes. But we also deployed them because this study is primarily interested in how racial prejudice erodes white support for pit bulls; and our prior research shows that these blatant measures of racial prejudice are unable to adequately identify racially sympathetic whites who may be more supportive of issues linked to African Americans [25,71].

We then augment our observational findings from the CCES and Lucid data with an original survey experiment to test H4’s causal claim that implicitly associating pit bulls with African Americans further erodes white support for the breed. The experiment was embedded into three of the Lucid surveys that we fielded in June 2020, July 2020 and August 2021 (pooled N = 3196). Our experimental design followed several prior studies, which all indirectly associated African Americans with specific policies through the racially evocative term “inner-city” [2,28,43].

Lastly, we test H5’s contention that states scoring high in racial prejudice will be significantly less likely to enact legislation preempting municipal pit bull bans with Fix and Mitchell’s [72] data on the twenty states who passed legislation preventing local governments from banning and regulating dogs solely based on breed (aka, pit bull protection laws) between 1989 and 2016. We then examined the relationship between passing pit bull protection laws and two different measures of state-level racial prejudice, both of which have been used and validated in prior research [73,74]. The first measure calculates each state’s level of white opposition to interracial dating from the Pew Values Survey cumulative file—a repeated cross-sectional survey that interviewed over 30,000 respondents from 1987 to 2012. The second follows Stephens-Davidowitz’s [74] approach and measures state-level prejudice with relative rates of racist Google searches for the “N-word”. The two measures are highly correlated with one another (r = .78), bolstering our confidence that both are tapping into state-level prejudice. We are also reassured by the fact that both measures of racial prejudice were more strongly associated with state-level opposition to Barack Obama in 2008 than John Kerry in the 2004 presidential election [73,74].

Racial prejudice and public opinion

Our first hypothesis posited that anti-Black attitudes should be a significant, independent, predictor of negative opinions about pit bulls. Consistent with H1’s expectations, unfavorable views of African Americans and OFR were significantly correlated with our four questions about pit bulls in both the CCES and Lucid data (see Table A1 in S1 Appendix).

But it’s important to account for other variables to test H1’s contention that racial prejudice is an independent predictor of public opinion about pit bulls. Our findings are robust to every possible specification we tried, so we selected our final model based on several factors. We followed Winter [2] and included favorability ratings of whites alongside favorability of African Americans to assess the relative influence of each variable while holding the other one constant. Partisanship is in the model to both account for its growing association with racial attitudes [25,75] and to determine the degree to which public opinion about pit bulls is rooted in party polarization. Our earlier discussion of pit bulls and masculinity prompted us to control for sex. We included education to control for its well-documented association with racial attitudes (correlation with OFR = -.17), and to assess how socioeconomic status is linked to public opinion about the breed. Finally, and most importantly, we included age to account for the fact that young people score significantly lower in racial prejudice (age is correlated with ORF at r = .28) and have much more favorable opinions of pit bulls than older Americans. Like most of the research we cited in the previous section on how racial attitudes are associated with public opinion about such issues as welfare, crime, drug addiction, health care, government spending and affirmative action, our analyses in this section are limited to whites. Including other races/ethnicities in the analysis, however, does not alter the substantive or statistical significance of the findings (see Table A4 in S1 Appendix).

Even after accounting for all those factors, Fig 3 shows that white Americans’ favorability ratings of African Americans were consistent predictors of support for pit bulls in both surveys. Across the eight dependent variables in the Lucid and CCES surveys, whites who rated African Americans very favorably were considerably more supportive of the breed. The display shows that moving from having a very unfavorable impression of African Americans to a very favorable impression increased sympathetic responses to those items from about 20 to 40 percentage points after controlling for favorability ratings of whites, partisanship, education, sex, and age. All eight relationships were highly significant, too, providing strong support for H1’s contention that anti-Black attitudes are correlated with unfavorable opinions of pit bulls. Moreover, the results in Fig 3 replicate across our other measure of overt racial prejudice—old-fashioned racism (see Table A3 in S1 Appendix).

Fig 3. Favorability ratings of African Americans predict white Americans’ support for pit bulls.

Fig 3

Note: Predicted probabilities are based on the logistic regression coefficients in Table A2 in S1 Appendix. Predicted probabilities were calculated by setting favorability rating of whites, partisanship, age, education level and gender to the mean white respondent. Sources: 2018 CCES Team Module; 2018–2021 Pooled Lucid Surveys; white respondents only.

The relationships in Fig 3, however, cannot tell us whether anti-Black attitudes are equally implicated in public opinion about all dog breeds. That seems unlikely in light of our earlier discussion of dog ownership being raced as white, but it’s still important to interrogate H2’s expectation that anti-Black attitudes are a significant predictor of rating pit bulls less favorably than other dog breeds. As noted above, we test this hypothesis with favorability ratings of pit bulls, Labradors, Golden Retrievers, German Shepherds, Collies, Huskies, Bulldogs, Dalmatians, Chihuahuas and dogs in general—that were included in all six Lucid surveys. We then scaled the non-pit bull dogs into a nine-item additive index of net dog favorability (Chronbach’s alpha = .82).

The first three columns of Table 1 regress our net dog favorability scale, net favorability ratings of pit bulls, and the difference between the two, on the same predictors used in Fig 2. We also control for favorability ratings of dogs in general, which was not asked in our CCES survey, to account for the fact that dog lovers also have much more positive views of pit bulls. The coefficients in Table 1 reveal that unfavorable impressions of African Americans, favorable views of whites, and older age were all significant predictors of rating pit bulls more negatively than other dog breeds. The results for favorable views of whites are consistent with the idea of dog ownership being generally raced as white in the U.S. and echo Winter’s [2] argument that “the racialization of Social Security turns on white Americans’ feelings about their own racial group because the policy is linked to white beneficiaries.” Meanwhile, the coefficients on Black favorability in Table 1 confirm H2’s suggestion that racial prejudice is an important predictor of pit bulls being rated less favorably than other dog breeds. Indeed, white Americans with a very unfavorable impression of African Americans rated other dog breeds much more favorably than pit bulls (+53 to -5 respectively) after holding the other variables in Table 1 at their means.

Finally, the last three columns of Table 1 test H3’s contention that exaggerated stereotypes of Black men as violent are significant predictors of public opinion about pit bulls. The fourth column shows that out of the six groups evaluated, only stereotypes of Black men as violent emerged as a significant predictor of holding less favorable views of pit bulls. Similarly, the last column of Table 1 shows that thinking African American men are violent was the only negative stereotype that significantly predicted rating pit bulls less favorably than other dog breeds. Those results both confirm H3’s expectations and speak to the importance of examining the racialization process through intersectional analyses of both race and gender schemas.

In sum, anti-Black attitudes are a remarkably consistent predictor of public opinion about pit bulls. Combining the results across twenty models from two different datasets in Table 1, Tables A2, and A3 in S1 Appendix shows that three blatant measures of racial prejudice—anti-Black affect, old fashioned racism, and negative stereotypes of Black men—are all significant predictors of harboring unfavorable opinions of the breed. Those results should not be susceptible to the same endogeneity issues as analyses of how racial attitudes predict public opinion about affirmative action, welfare, and Donald Trump [69,75,76], either, since pit bulls probably aren’t salient enough to alter feelings towards African Americans. Nor is omitted variable bias a threat to the validity of our findings. Aside from age, including additional factors (e.g. income, region, homeownership etc.) in our analyses never weakened the results. You can see in the tables, in fact, that normally potent sociopolitical and socioeconomic predictors of public opinion (e.g. partisanship and education) are unrelated to views of pit bulls. The findings, instead, indicate that pit-oriented opinions have much more to do with racial and generational dynamics than partisan and economic polarization.

Implicit racialization and public opinion

The results presented thus far suggest that the racialization of pit bulls has eroded public support for the breed. So does the fact that the majority of Americans who think of pit bulls as Black-owned dogs harbor more negative opinions of the breed. In our Lucid surveys, for example, 60 percent of respondents who thought white people were more likely to own pit bulls rated the breed favorably, compared to 47 percent of those who think of pit bulls as a Black-owned breed.

Those findings fit a familiar pattern. We noted earlier that overestimating the share of violent crime committed by African Americans is associated with support for more punitive criminal justice polices [21]. Likewise, our analysis of a November 2017 Poll conducted by Survey Sampling International (raw data accessed from the Roper Center), found that 44% of whites who said “poor Black people are more likely to benefit from welfare programs than poor white people” wanted funding for welfare programs to be decreased, compared to just 28% of whites who didn’t think that welfare disproportionately benefits African Americans. And only 26% of whites who thought Obama’s health care proposals favored Blacks over whites supported his universal health care plan, compared to 61% support among whites who didn’t think Obamacare would disproportionately benefit African Americans [25].

But the observational nature of these correlations makes it difficult to establish any causal role of racialization in public opinion. So, we tested H4’s causal claim that implicitly associating pit bulls with African Americans further erodes white support for the breed by embedding an experiment into three of the Lucid surveys that we fielded in June 2020, July 2020 and August 2021 (pooled N = 3196). Our experimental design followed several other studies, which all implicitly associated African Americans with specific policies through the racially evocative term “inner-city.” The inner-city frame is particularly relevant for our purposes since it closely mirrors the way in which scholars and journalists contend that pit bulls have been racialized in media and popular culture. “Once the pit bull was portrayed as an ‘inner-city dog,’ Dickey [18, pg 146] for instance stated, “it became a magnet for racial fears about crime and the American underclass.” Consistent with that contention, Americans greatly exaggerate the share of Black people living in those urban areas [28], making “inner-city” a powerful race-coded cue. So much so that prior experiments, which use “cities” to implicitly prime race, have altered public opinion about criminal justice policies, education spending, and the minimum wage [2,28,43].

The results in Fig 4 show that implicitly associating African Americans with pit bulls via the “inner city” treatment also significantly decreased white Americans’ support for legalizing the breed. The left-hand side of the display shows that 67.1% of white respondents said it should be legal to own pit bulls in the baseline wording, compared to only 54.5% of whites in the inner-city condition. That 12.6 percentage-point difference between conditions was very highly significant, too (T = 6.3, see Table A5 in S1 Appendix), and therefore supports H4’s expectations. The right-hand side of the display, meanwhile, shows that non-whites’ positions were statistically equivalent regardless of whether they received the inner-city question wording. In fact, we can be quite confident that whites were more heavily influenced by the inner-city treatment than non-whites (p = .006, see Table A3 in S1 Appendix). The highly significant negative interaction here between inner-city*white dovetails with prior experimental research showing that implicit race associations like inner-city are more potent in public opinion for whites than Black Americans [54]; and it suggests that our intended racialization experiment is tapping into something distinctly racial.

Fig 4. Opinions of pit bull legalization by race and experimental condition.

Fig 4

The baseline condition asked, “Do you think that it should be legal or illegal to own a pit bull?” The inner-city condition asked, “Do you think that it should be legal or illegal to own a pit bull in inner-city neighborhoods?” Source: Pooled Lucid Surveys, June 2020, July 2020, August 2021.

Contrary to some prior research, however, unfavorable views of African Americans were not significantly stronger predictors of support for banning the breed in the inner-city condition than they were in the baseline group. This null effect for the inner-city*Black favorability interaction most likely stems from the fact that racial attitudes were already associated with public opinion about pit bulls to begin with. Experiments generally produce weaker racial priming effects on issues that were already racialized [2,25,52]; and we know from the prior sections that most Americans already think of pit bulls through a racialized prism. Interaction effects are also much more difficult to detect statistically [77], as it takes “16 times the sample size to estimate an interaction than to estimate a main effect” [78]. We’re especially encouraged, then, by the highly significant interaction between inner-city*white in our experimental results.

But it could still simply be the case that whites evaluate just about any issue or policy less favorably that’s implicitly associated with African Americans via inner-city connotations. A recently published article on “Racialized Names and Time to Adoption in a County Dog Shelter,” however, shows that implicit associations with African Americans are particularly powerful for pit bulls. “Pit bulls with increasingly Black-sounding names were adopted significantly slower,” the study found, “suggesting that adopters were resistant to dogs with Black-sounding names but only when their breed [of pit bull] made race particularly salient” [79, pg. 227]. We suspect that connecting pit bulls to inner cities makes race similarly salient in eroding white support for these dogs.

Yet while the results are consistent with both that interpretation and prior research on how racialization erodes white support for issues and policies associated with African Americans, it is important to conclude here by noting that we cannot say for certain what the exact mechanism is behind why pit bulls are less popular when they’re framed as inner-city dogs. It’s possible, for instance, that there’s less support for large, muscular dogs in cities because people think they need more space to flourish. So, we hope that future research will build on these results by further examining how and why implicit associations with African Americans erode whites’ support for legalizing pit bulls.

Racial prejudice and policies across the states

We noted earlier that the racialization of public opinion often has important policy consequences; and our final hypothesis suggested that the same might be true for pit bulls. To test that contention, Fig 5 displays the relationship between enacting pit bull protection laws and the two different measures of state-level racial prejudice discussed in the data and methods section. You can see that both of those measures—state-level opposition to interracial dating and relative rates of racist Google searches—powerfully predict differences in breed specific legislation (BSL) across the states. Fig 5 shows that states with low levels of racial prejudice had roughly an even chance of passing BSL preemption laws. But those probabilities sharply decline in both displays as we move across the spectrum towards more racially prejudiced states like West Virginia and Mississippi. The negative relationships between racial prejudice and BSL preemption laws in the two displays are both statistically significant, as well, even with the small number of cases in the analysis (see Table A6 in S1 Appendix).

Fig 5. State-level racial prejudice negatively predicts which states have passed laws preempting breed-specific legislation.

Fig 5

Note: Analysis limited to continental United States. Lines are smoothed averages (bandwidth = .80) Source: Data on state laws from Fix and Mitchell; state-level white opposition to interracial dating from the 1987–2012 Pew Values Survey Merged File; data on racist searches are from Google Trends, 2004–2019.

Those significant negative relationships remain mostly intact after accounting for other factors. The full results in Table A6 in S1 Appendix, for example, show that controlling for state-level attitudes from the Pew data, such as white partisanship and white support for limited government, neither reduced the substantive importance nor the statistically significant relationships between state-level prejudice and pit bull policies. Including each state’s Black population percentage introduces more uncertainty into the small-N analyses because it’s highly correlated with both measures of state-level prejudice (r = .57 and r = .58 respectively). Yet even with that multicollinearity, state-level racist Google searches remain a significant negative predictor of passing BSL preemption laws (p = .025); and white opposition to interracial dating just misses the mark (p = .15).

So, while there’s necessarily more uncertainty in these small-N state-level analyses than in our large-N survey results, the results generally confirm H5’s expectations that racially prejudiced states are less likely to enact legislation protecting pit bulls from local bans on the breed. They also amplify prior research on how policies, such as crime, welfare, and Medicaid, tend to be implemented across the states in ways that reflect their underlying racialization.

Conclusion

Taken together, the results in this article confirm what many keen observers of the pit bull’s position in American society have long suspected: Pit bull prejudice is at least partly an extension of racial prejudice that’s activated by the breed’s affiliation with Black men and African American culture. While that’s certainly significant, the article’s more important contribution comes from what these dogs can teach us about racial politics. By providing a novel empirical application that synthesizes and extends existing research on how the racialization process affects public opinion and policy implementation across the states, our analyses of pit bulls provide broader insights into the ongoing power of anti-Blackness in American politics.

Indeed, we’ve uncovered some strong similarities between the racial politics surrounding pit bulls and the well-documented racialization of other ostensibly non-racial issues, such as crime and welfare. In each instance, there is some empirical link between African Americans and the issue. African Americans are more likely to be incarcerated, receive welfare, and to interact with pit bulls than white people. But those associations are then framed in an especially negative light by the news media, which in turn erodes racially prejudiced whites’ support for welfare, compassionate criminal justice policies, and pit bulls. The implementation of these racialized policies across the states then reflects their underlying racialization, as the most racially prejudiced states have less generous welfare benefits, more punitive crime policies, and fewer pit bull protection laws. To be sure, racialization is far from the only reason why so many people dislike pit bulls—and it may not even be the most important factor. But the results in the article indicate that it’s impossible to disentangle pit bull politics from the politics of race.

Well, up until very recently at least. Unlike the enduring associations between African Americans and issues like welfare and crime, the racialization of pit bulls appears to be changing rather rapidly. While the news media’s stories about pit bulls have been consistently negative, our related research shows that depictions of pit bulls on social media are tremendously positive [39]. So much so, that there are actually more positive tweets and Instagram posts about pit bulls than there are about any other dog breed. That positive imagery predominantly has a white face attached to it, as pit bull positivity on social media is overwhelmingly propagated by white advocates doting on the breed [10,39].

The changing face of “pit bull people” from Black to white Americans is making the breed more popular, too—much the way that white people have become more supportive of drug treatment now that the face of the opioid epidemic is increasingly white [34]. In fact, our subsequent research shows that public opinion is increasingly shifting in favor of pit bulls; and more significantly, that the racialized (white) pit bull positivity that characterizes so much social media content has disproportionately affected white Americans’ opinions of the breed. Like other prominent issues, pit bull negativity is racialized as Black but pit bull positivity has a white face.

Supporting information

S1 Appendix

(DOCX)

pone.0305959.s001.docx (61.7KB, docx)
S1 File

(ZIP)

pone.0305959.s002.zip (5.8MB, zip)

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Kim, Claire Jean. 2015. Dangerous Crossings: Race, Species and Nature in a Multicultural Age. Cambridge University Press, 2015.
  • 2.Winter, Nicholas J.G. 2008. Dangerous frames: How Ideas about Race & Gender Shape Public Opinion. University of Chicago Press.
  • 3.Gilens, Martin. 1999. Why Americans Hate Welfare: Race, Media, and the Politics of Antipoverty Policy. University of Chicago Press.
  • 4.Mendelberg, Tali. 2001. The Race Card. Princeton: Princeton University Press.
  • 5.Gilliam Franklin D. Jr, and Shanto Iyengar. 2000. "Prime Suspects: The influence of local television news on the viewing public." American Journal of Political Science. 44(3): 560–573. [Google Scholar]
  • 6.Soss, Joe, Richard C. Fording, and Sanford F. Schram. 2011. Disciplining the poor: Neoliberal Paternalism and the Persistent Power of Race. University of Chicago Press.
  • 7.Gunter Lisa M., Barber Rebecca T., and Wynne Clive DL. 2016. "What’s in a name? Effect of Breed Perceptions & Labeling on Attractiveness, Adoptions & Length of Stay for Pit-bull-Type Dogs." Plos one 11(3). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Gunter Lisa M., Barber Rebecca T., and Wynne Clive DL. 2018. "A canine identity crisis: Genetic breed heritage testing of shelter dogs." PloS one (13)8. doi: 10.1371/journal.pone.0202633 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Balko, Radley. 2016. “The Dirty Secret Behind Banning Certain Dog Breeds.” Washington Post. https://www.washingtonpost.com/news/the-watch/wp/2016/10/26/the-dirty-secret-behind-banning-certain-dog-breeds/
  • 10.Guenther, Katja M. 2022. The lives and deaths of shelter animals: the lives and deaths of shelter animals. Stanford University Press.
  • 11.Boisseron, Bénédicte. 2018. Afro-Dog: blackness and the animal question. Columbia University.
  • 12.Thompson Andrew J., Pickett Justin T., and Intravia Jonathan. 2022. "Racial stereotypes, extended criminalization, and support for Breed-Specific Legislation: experimental and observational evidence." Race and Justice 12(2): 303–321. [Google Scholar]
  • 13.Mayorga‐Gallo Sarah. 2018. "Whose best friend? Dogs and racial boundary maintenance in a multiracial neighborhood." In Sociological Forum 33(2): 505–528. [Google Scholar]
  • 14.Coppock Alexander, and McClellan Oliver A. 2019. "Validating the demographic, political, psychological, and experimental results obtained from a new source of online survey respondents." Research & Politics 6(1). [Google Scholar]
  • 15.Griffin, Robert. 2019. “A Closer Look at the Methodology of the Nationscape.” Democracy Fund/Voter Study Reports. https://www.voterstudygroup.org/blog/a-closer-look-at-the-methodology-of-nationscape.
  • 16.Pew Research Center. 2006. “Dogs Edge Cats (Dads Trail Both).” https://www.pewresearch.org/wp-content/uploads/sites/3/2010/10/Pets.pdf.
  • 17.USDOJ Civil Rights Division. 2015. The Ferguson Report: Department of Justice Investigation of the Ferguson Police Department. https://www.justice.gov/sites/default/files/opa/press-rele7ases/attachments/2015/03/04/ferguson_police_department_report.pdf.
  • 18.Dickey, Bronwen. 2017. Pit Bull: The battle over an American icon. Vintage.
  • 19.Kalof Linda, and Taylor Carl. 2007. "The discourse of dog fighting." 2007. Humanity & Society 31(4): 319–333. [Google Scholar]
  • 20.Nast, Heidi J. 2015. "Pit bulls, slavery, and whiteness in the Mid-to Late-Nineteenth-century US: Geographical trajectories; primary sources." In Critical animal geographies, pp. 127–146. Routledge.
  • 21.Chiricos Ted, Welch Kelly, and Gertz Marc. 2004. "Racial typification of crime and support for punitive measures." Criminology 42(2): 358–390. [Google Scholar]
  • 22.Tesler Michael. 2020. “Rafael Warnock’s Dog Ads Cut Against White Voters’ Stereotypes of Black People.” FiveThirtyEight. December 15, 2020. [Google Scholar]
  • 23.Sears, David O. 1993. Symbolic Politics: A Socio-Psychological Theory. In Explorations in Political Psychology, ed. Shanto Iyengar and William J. McGuire, 113–49. Durham, NC: Duke University Press.
  • 24.Kinder, Donald R., and Allison Dale-Riddle. 2011. The end of race?: Obama, 2008, and racial politics in America. Yale University Press.
  • 25.Tesler, Michael. 2016. Post-Racial or Most-Racial? Race and Politics in the Obama Era. University of Chicago Press.
  • 26.Henderson Michael, and Hillygus D. Sunshine. 2011. "The dynamics of health care opinion, 2008–2010: Partisanship, self-interest, and racial resentment." Journal of Health Politics, Policy and Law 36(6): 945–960. doi: 10.1215/03616878-1460533 [DOI] [PubMed] [Google Scholar]
  • 27.Knowles Eric D., Lowery Brian S., and Schaumberg Rebecca L. 2010. "Racial prejudice predicts opposition to Obama and his health care reform plan." Journal of Experimental Social Psychology 46(2): 420–423. [Google Scholar]
  • 28.Hurwitz Jon and Peffley Mark. 2005. Playing the Race Card in the Post–Willie Horton Era: The Impact of Racialized Code Words on Support for Punitive Crime Policy” Public Opinion Quarterly 69(1): 99–112. [Google Scholar]
  • 29.Fishman, Laura T. 1998. “The Black Bogeyman and White Self-Righteousness. In Coramae Richey Mann and Marjorie S. Zatz (eds.) Images of Color, Images of Crime. Roxbury Publishing Company.
  • 30.Cohen, Andrew. 2015. “How White Users Made Heroin a Public Health Problem.” The Atlantic. https://www.theatlantic.com/politics/archive/2015/08/crack-heroin-and-race/401015/.
  • 31.Stroud, Hernandez. D. 2016. “Our Opioid Crisis Reveals Deep Racial Bias in Drug Treatment.” Time Magazine. https://time.com/4385588/crack-babies-heroin-crisis/.
  • 32.Lopez, German. 2017. “When a Drug Epidemic’s Victims are White.” Vox. https://www.vox.com/identities/2017/4/4/15098746/opioid-heroin-epidemic-race
  • 33.McLean Katherine. 2017. "From “junkies” to “soccer moms”: Newspaper representations of overdose, 1988–2014." Critical criminology 25(3): 411–432. [Google Scholar]
  • 34.Raychaudhuri Tanika, Mendelberg Tali, and McDonough Anne. 2023. "The political effects of opioid addiction frames." The Journal of Politics 85(1): 166–177. [Google Scholar]
  • 35.Pettigrew Thomas F. 1979. "The ultimate attribution error: Extending Allport’s cognitive analysis of prejudice." Personality and social psychology bulletin 5(4): 461–476. [Google Scholar]
  • 36.Iyengar Shanto. 1990. "Framing responsibility for political issues: The case of poverty." Political behavior 12(1): 19–40. [Google Scholar]
  • 37.Ben-Porath Eran N., and Shaker Lee K. "News images, race, and attribution in the wake of Hurricane Katrina." Journal of Communication 60(3): 466–490. [Google Scholar]
  • 38.Entman, Robert M., and Andrew Rojecki. 2001. The Black Image in the White Mind: Media and Race in America. University of Chicago Press.
  • 39.McThomas, Mary and Michael Tesler. 2024. The Racial Politics of Pit Bulls. Book manuscript in progress. University of California, Irvine.
  • 40.Mendelberg Tali. 2008. “Racial Priming Revived.” Perspectives on Politics 6(1):109–23 [Google Scholar]
  • 41.Tesler, Michael. 2018 "Racial priming with implicit and explicit messages." In Oxford Research Encyclopedia of Politics.
  • 42.Kellstedt, Paul M. 2003. The mass media and the dynamics of American racial attitudes. Cambridge University Press.
  • 43.Kinder, Donald R., and Cindy D. Kam. 2009. Us Against Them: Ethnocentric Foundations of American Opinion. University of Chicago Press.
  • 44.Soss Joe, Langbein Laura, and Metelko Alan R. 2003. "Why do white Americans support the death penalty?." The Journal of Politics 65(2): 397–421 [Google Scholar]
  • 45.Peffley Mark and Hurwitz Jon. 2010. Justice in America: The Separate Realities of Blacks and Whites. New York: Cambridge University Press. [Google Scholar]
  • 46.Hutchings Vincent. 2015. "Race, punishment, and public opinion." Perspectives on Politics. 13(3): 757–761. [Google Scholar]
  • 47.McConnaughy, Corrine M. and Ismail White. 2011. “Racial Politics Complicated: The Work of Gendered and Race Cues in American Politics.” New Research on Gender and Political Psychology Conference. Rutgers University, March 4–5, 2011. https://polisci.osu.edu/sites/polisci.osu.edu/files/mcconnaughy_white.pdf
  • 48.Daniel Myers, C., Zhirkov Kirill, and Trujillo Kristin Lunz. 2024. "Who Is “On Welfare”? Validating the Use of Conjoint Experiments to Measure Stereotype Content." Political Behavior 46(1): 89–110. [Google Scholar]
  • 49.Barak Gregg. 1994. "Between the waves: Mass-mediated themes of crime and justice." Social justice 21(3): 133–147. [Google Scholar]
  • 50.Quillian Lincoln, and Pager Devah. 2001. "Black neighbors, higher crime? The role of racial stereotypes in evaluations of neighborhood crime." American journal of sociology. 107(3): 717–767. [Google Scholar]
  • 51.Federico Christopher M. 2004. "When do welfare attitudes become racialized? The paradoxical effects of education." American Journal of Political Science 48(2): 374–391. [Google Scholar]
  • 52.Huber Gregory. A., and John Lapinski. 2006. “The ‘Race Card’ Revisited: Assessing Racial Priming in Policy Contests.” American Journal of Political Science 50(3): 421–40. [Google Scholar]
  • 53.Filindra Alexandra, and Kaplan Noah J. 2016. "Racial resentment and whites’ gun policy preferences in contemporary America." Political behavior 38,(2): 255–275. [Google Scholar]
  • 54.White Ismail K. 2007. ‘‘When Race Matters and When It Doesn’t: Racial Group Differences in Response to Racial Cues.” American Political Science Review 101(2): 339–54. [Google Scholar]
  • 55.Stephens-Dougan L. 2023. “White Americans’ reactions to racial disparities in COVID-19.” American Political Science Review, 117(2):773–780 [Google Scholar]
  • 56.Reingold Beth, and Smith Adrienne R. "Welfare policymaking and intersections of race, ethnicity, and gender in US state legislatures." American Journal of Political Science 56(1):131–47. [DOI] [PubMed] [Google Scholar]
  • 57.Lanford Daniel, and Quadagno Jill. 2016. "Implementing ObamaCare: The politics of Medicaid expansion under the Affordable Care Act of 2010." Sociological Perspectives 59:619–639. [Google Scholar]
  • 58.Johnson Martin. 2001. "The impact of social diversity and racial attitudes on social welfare policy." State Politics & Policy Quarterly 1(1): 27–49. [Google Scholar]
  • 59.Fusaro Vincent A. "State politics, race, and ‘welfare; as a funding stream: Cash assistance spending under temporary assistance for needy families." Policy Studies Journal 49(3): 811–834. [Google Scholar]
  • 60.Grogan Colleen M. and Park Sunggeun Ethan. 2017. "The racial divide in state Medicaid expansions." Journal of Health Politics, Policy and Law 42(3): 539–572. doi: 10.1215/03616878-3802977 [DOI] [PubMed] [Google Scholar]
  • 61.Fellowes Matthew C., and Rowe Gretchen. 2004. "Politics and the new American welfare states." American Journal of Political Science 48(2): 362–373. [Google Scholar]
  • 62.Keiser Lael R., Mueser Peter R., and Choi Seung‐Whan. "Race, bureaucratic discretion, and the implementation of welfare reform." 2004. American Journal of Political Science 48(2): 314–327. [Google Scholar]
  • 63.Jacobs David, and Carmichael Jason T. 2002. "The political sociology of the death penalty: A pooled time-series analysis." American Sociological Review (1):109–131. [Google Scholar]
  • 64.Pritchard Anita, and Wiatrowski Michael. 2008. "Race and capital punishment: State level analysis of the effects of race on states’ capital punishment policies." Journal of Ethnicity in Criminal Justice 6(2): 103–121. [Google Scholar]
  • 65.Baumgartner Frank R., Box-Steffensmeier Janet M., Campbell Benjamin W., Caron Christian, and Sherman Hailey. 2020. "Learning to kill: Why a small handful of counties generates the bulk of US death sentences." PloS one 15(10). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Percival Garrick L. 2009. "Testing the impact of racial attitudes and racial diversity on prisoner reentry policies in the US states." State Politics & Policy Quarterly 9(2): 176–203 [Google Scholar]
  • 67.Swanson, Emily 2014. “There’s Still A lot of Work to be Done for Pit Bulls, Poll Finds.” HuffingtonPost. https://www.huffpost.com/entry/pit-bulls-poll_n_5628261
  • 68.Tesler Michael. 2013. "The Return of Old-Fashioned Racism to White Americans’ Partisan Preferences in the Early Obama Era." The Journal of Politics 75(1): 110–123 [Google Scholar]
  • 69.Sniderman, Paul M., and Edward G. Carmines. 1997. Reaching Beyond Race. Harvard University Press
  • 70.Carmines Edward G., Sniderman Paul M., and Easter Beth C. 2011. "On the meaning, measurement, and implications of racial resentment." The Annals of the American Academy of Political and Social Science 634(1): 98–116. [Google Scholar]
  • 71.Tesler, Michael and David O. Sears. 2015. “How Standard Streotype Scales Underestimate the Political Impact of Racial Attitudes. Presented at annual meeting of the American Political Science Association.
  • 72.Fix Michael P., and Mitchell Joshua L. 2017. "Examining the Policy Learning Dynamics of Atypical Policies with an Application to State Preemption of Local Dog Laws." Statistics, Politics and Policy 8(2): 223–247 [Google Scholar]
  • 73.Highton Benjamin. 2011. "Prejudice Rivals Partisanship and Ideology When Explaining the 2008 Presidential Vote Across the States." PS Political Science and Politics 44(3): 530–537. [Google Scholar]
  • 74.Stephens-Davidowitz Seth. 2014. "The cost of racial animus on a black candidate: Evidence using Google search data." Journal of Public Economics 118: 26–40. [Google Scholar]
  • 75.Griffin, Robert, Mayesha Quesem, John Sides and Michael Tesler. 2021. “Racing Apart: Partisan Shifts on Racial Attitudes Over the Past Decade.” Democracy Fund/Voter Study Reports.
  • 76.Goren Paul. 2022. "Pliable prejudice: The case of welfare." American Journal of Political Science 66 (4):961–976. [Google Scholar]
  • 77.McClelland Gary H., and Judd Charles M. 1993. "Statistical difficulties of detecting interactions and moderator effects." Psychological Bulletin 114(2): 376. doi: 10.1037/0033-2909.114.2.376 [DOI] [PubMed] [Google Scholar]
  • 78.Gelman, Andrew, Jennifer Hill, and Aki Vehtari. 2020. Regression and other stories. Cambridge University Press.
  • 79.Quadlin Natasha, and Montgomery Bradley. 2022. "When a Name Gives You Pause: Racialized Names and Time to Adoption in a County Dog Shelter." Social Psychology Quarterly 85(2): 210–235 [Google Scholar]

Decision Letter 0

Hans H Tung

10 Oct 2023

PONE-D-22-34733The Racialization of Pit Bulls: What Dogs Can Teach Us About Racial PoliticsPLOS ONE

Dear Dr. Tesler,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. As you can see from the reviewers' reports, reviewers were generally positive about the paper but also raised various issues about the methods you used and the way in which data and results were presented. Please revise your manuscript according to their suggestions. 

Please submit your revised manuscript by October 25. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Hans H. Tung

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

3. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

Note from the PLOS Editorial Office: Please note that reviewer 1 is Justin T Pickett, who has agreed to be named as a reviewer.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Partly

********** 

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

********** 

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

********** 

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

********** 

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is a fantastic study that has one major flaw: The authors have ignored extremely relevant prior research. And that is totally unacceptable. I will give a clear example, if you go to Google scholar and search for "racial attitudes pit bull," the very first study returned (Thompson et al., 2022) is an experiment that did almost exactly what the current study does (but found different results). It developed the theory for why racial attitudes should be related to views about pit bulls and breed-specific legislation, it measured peoples' perceptions of the racial composition of pit bull owners, it tested whether you could prime racial concerns and influence support for breed-specific legislation, and it also examined the relationship between racial attitudes and views about breed-specific legislation.

True, the current submission is a MUCH better study than Thompson et al. (2022). The former used a smaller sample, weaker measures, and focused only on college students. Still, it is wild that the current authors fail to cite or discuss the earlier study. That is not how science is supposed to work and I expect better. The current authors need to cite Thompson et al. (2022), they need to discuss the findings in that study, and they need to explain how their study goes beyond it and offer some explanation for why the findings in it are different than the earlier ones.

Given the current authors' focus on the perceived racial composition (or racial typification) of dog owners (e.g., Figure 2), I would also direct them, when talking about the racialization of crime (pp. 8-11), to the extensive work on how racial typification of crime (i.e., the perceived racial composition of criminals) is related to support for harsh policies. The authors should start with Chiricos et al.'s (2004) seminal study and go from there in their literature review. The problem is that authors, for reasons that defy logic, have ignored all the relevant public opinion work by scholars like Ted Chiricos and Frank Cullen. The latter, for example, has several important review articles on racial attitudes and criminal justice attitudes (e.g., Cullen et al., 2021). Science is supposed to be cumulative, and the current authors should act like it.

REFERENCES

Chiricos, Ted, Kelly Welch, and Marc Gertz. 2004. Racial typification of crime and support for punitive measures. Criminology 42: 358-390.

Cullen, Francis T., Leah C. Butler, and Amanda Graham. 2021. Racial attitudes and criminal justice policy. Crime and justice, 50(1), 163–245.

Thompson, Andrew J., Justin T. Pickett, and Jonathan Intravia. 2022. Racial Stereotypes, Extended Criminalization, and Support for Breed-Specific Legislation: Experimental and Observational Evidence. Race and Justice 12: 303-321.

Note from the PLOS Editorial Office: Please note that reviewer 1 is Justin T Pickett, who has agreed to be named as a reviewer.

Reviewer #2: This paper studies the racialization of attitudes regarding pit bulls in the United States. More specifically, the paper proposes that negative attitudes toward pit bulls, and a willingness to ban them or otherwise strictly regulate them, are rooted, at least partly, in implicit associations between the breed and African Americans. Thus, the authors argue, those with negative attitudes toward African Americans as a group are more likely than others to have negative attitudes toward pit bulls. The authors present a wealth of survey, media, experimental and policy-outcome evidence in support of their argument. By and large, this is done extremely well and is generally convincing. That said, there are certain problems that I would like the authors to address before I can recommend publication. I also note a number of minor points for the authors at the end of the review.

Before discussing the problems, I should say first that the authors had me at the survey data: that is, I am fully persuaded by the analysis in the “Racial prejudice and public opinion” section. For one thing, I find it very hard to imagine that the relationship between racial and pit bull attitudes runs in the opposite direction. For another, I cannot think of any important omitted variable that isn’t quite closely related to something the authors already control for in some model. For instance, whites (and so those with lower levels of favorability toward African Americans) probably have more past negative experience with dogs (because they are more likely to own and interact with them). But past negative experience is presumably correlated with dog favorability, which is controlled in models reported in Table 1. Anyway, I think the authors could make more of the (many) reasons why we should take their correlational evidence very seriously.

As regards the problems, first, the analysis of coverage of pit bulls isn’t very convincing. It seems to me that the burden of this analysis is to show that coverage of pit bulls – and perhaps, by extension, wider cultural discourse concerning dogs – associates the breed with African Americans very prominently or regularly. But it’s only the very rare pit bull story that mentions African Americans, about 2%. I don’t know exactly how to calibrate this percentage, but it doesn’t sound very high to me. The authors need to provide some basis for thinking that this percentage indicates that associations between pit bulls and African Americans are sufficiently pervasive in the culture that we should expect views of pit bulls to be racialized.

Relatedly, I don’t follow the authors’ analysis of dog-news sentiment. Figure 3 essentially depicts an interaction, with respect to tone, between the type of dog in a story and whether African Americans are mentioned. It seems to me that the observed interaction is the reverse of what we’d expect, under the authors’ argument. That is, if pit bulls were especially affected by association with African Americans, then I would expect the relative impact of that association on sentiment to be greater for pit bulls than for other dogs. But that’s not the case here: for non-pit bulls, association with African Americans increases the negativity of net sentiment by about 60%; for pit bulls, the comparable effect is about 40%.

My other significant concern involves the experimental evidence. I accept that it supports the authors’ hypothesis (H5), but that hypothesis isn’t actually a very specific test of their argument. And other analysis of the experiment seems to threaten the authors’ interpretation of this effect in terms of racialization. Specifically, the inner-city treatment doesn’t increase the impact of racial attitudes (black favorability) on pit bull attitudes – and this is precisely the effect the authors need to establish, i.e., implicitly associating pit bulls with African Americans increases the weight of racial attitudes in pit bull attitudes. Does the interaction between racial attitudes and the treatment at least reach significance among whites?

I have a number of smaller comments below.

- On p. 11, H4 proposes that “stereotypes of Black men as violent will be particularly potent predictors of rating pit bulls unfavorably”. This wording is somewhat vague, but I presume the authors mean something like the effects of these attitudes are stronger than those for other racial attitudes (group favorability, etc.). The authors conclude (pp. 19-21) that the analysis supports their hypothesis. But I see no test here that compares effects across models or otherwise speaks to the “particular potency” of these stereotypes as a determinant of pit bull attitudes.

- On p. 13, the reference to Figure A2 should be to A1.

- At the top of p. 21, the reference to H5 should be to H4.

Reviewer #3: Overall, I think this paper provides strong evidence of a correlation between attitudes towards African-Americans and towards pitbulls, as well as state levels correlation of behavioral measure of attitudes (online searches) to laws banning pitbulls. There is also media and experimental evidence, but are more equivocal, and its difficult to separate competing explanations.

Main comments:

1)

I don’t think Figure 3 (media) supports the thrust of the argument. Stories about pitbulls mentioning African Americans are more negative – but so are stories about non-pitbulls. This could be straightforward anti-Black racism in the media, with no special link to pitbulls. And pitbull stories are more negative than other dogs, with or without mentioning African-Americans, consistent with pitbulls being (perceived to be) more violent regardless of their owners. Looking at the appendix, stories with Rottweilers are more likely to mention Black people then those with pit bulls! This doesn’t mean the theory is necessarily false given the potential implicit associations etc, but it does need to be acknowledged that this evidence is perhaps suggestive, but not watertight.

2)

Similarly, the experiment says that “unfavorable views of African Americans were not significantly stronger predictors”. I assume this is the result of another model with an interaction to look at heterogeneous effects, although that’s not clear. More importantly, it’s true that experiments trying to prime something that is already salient can have null or small effects. If pitbulls are already highly racialized, then asking about pitbulls will already prime racial attitudes, and adding “inner-city” can’t add much more. However, there is clearly an effect from the inner city treatment! I presume what is happening is that everyone shifts toward banning, not just people with negative racial attitudes. This is a problem for the theory, if people move but not in the direction of their racial attitudes.

Perhaps this is because the results are actually not because of race. Maybe people think its ok to own large and aggressive dogs out in rural areas, where there is lots of space, might be needed to guard animals, etc. They are not good in the city, with crowds of people, small apartments, public transit, etc. I bet you could get the same result asking about bans on large pick-up trucks. Or, perhaps this is about location: racial attitude are confounded with geography, and people are fine with pitbulls “over there”, but don’t want them in their own suburbs.

Regardless, it would be best to up-front about these null results, show it in a figure (so we can see the Cis) and discuss possibilities. Is it because of a non-racial effect, or countervailing confounding? Or measurement issues, due to blunt racial attitude questions (maybe the priming happens among people with weakly negative racial attitudes). Maybe its just power: interaction analyses are extraordinarily power-hunger. Including it in the abstract might be good too. Then we can all better learn from this, and people can do follow-up studies which cite this paper.

3)

Why are only whites included in the surveys starting on p.15? Surely the attitude structure of non-whites is the same: they associate African-Americans with pitbulls, so their views toward them is partly a function of views toward African-Americans. If its specifically anti-black views that matter here, there are certainly Latino and Asian Americans with anti-black views. Plus Figures 1 and 2 include all respondents, and they’re analyzed separately in Figure 5. On the other hand, its possible that there are ceiling effects going on, because of the racial attitude questions used. I think the authors should include all respondents, including non-white ones. Or if they have some strong theoretical reason for excluding them, at least a set of models including them in in the appendix and include a footnote telling the reader the results.

4)

Justify the control variables. There is an awful lot of research arguing partisanship is a product of racial attitudes. I’m not sure what including attitudes toward whites would do to the model, but its not clear what its purpose is. And there is no control for income, which is pretty standard and also correlated with dog ownership. See Lenz and Sahn 2020 on related issues. I think the authors should do a bivariate model, and report if the results are very different or not, and if so then which control variables make the big difference. Or, they could put some significant work into justifying why these control variables are really needed, and others not.

Some smaller issues:

Research on racialization, such as Tesler and others, has emphasized that those with positive (pro-Black) racial attitudes become more positive toward racialized issues. Is that the case here? Similerly, the paper makes various claims, such as “the racialization of pit bulls has eroded public support for the breed”. Has it? Or has it just made some people like them more, and others less.

Its good to report on the discussion of the racial attitude measure, that its less correlated with other social attitudes etc. Its not obvious that this is a good thing, or that it will result in conservative estimates. What we really want is a true measure of racial attitudes. I’m no expert, but I wouldn’t assume attenuation bias, since the error isn’t random just noise, its concentrated at one end of the scale. The authors could look carefully at the methodological research on this. Or, they could just point out the properties of the measures used, and say they aren’t sure exactly what effects this could have.

What are the potential generalizability of these findings? As I’m writing this, I noticed that the UK is going to ban the related breed “American XL Bully”. And after some quick googling, it seems like in other countries including Australia and Canada there are also debate about bans on pitbulls. The authors may not be claiming direct evidence, but given that anti-Black racism and pitbull bans both occur in many countries, it seems worth discussing.

My own experience with lucid is the data is quite low quality, worse than other online platforms. What kind of measure did the authors take? Include that somewhere (unless I missed it). Does excluding low quality respondents change the results?

********** 

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: J. Scott Matthews

Reviewer #3: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Jun 28;19(6):e0305959. doi: 10.1371/journal.pone.0305959.r002

Author response to Decision Letter 0


22 Nov 2023

Comments to the Editor

Thank you very much for the opportunity to revise and resubmit our manuscript with minor revisions. We have worked hard to address all the reviewers’ critiques and to incorporate their thoughtful suggestions into the revised manuscript.

More specifically, you’ll see from our memo that we have now engaged with the relevant literature that we regrettably omitted from the first submission, deemphasized the automated sentiment analyses, added some key details about measures and results in accordance with the reviewers’ advice, and further qualified our experimental findings with some new caveats. We hope that these changes have now made the manuscript suitable for publication in PLOS ONE.

Response to Reviewer 1

Thanks so much for the very helpful suggestions about relevant literature to incorporate into the revised manuscript. We regret these omissions from the prior submission and the revised manuscript now cites these studies in detail, paying particularly close attention to Thomspon et al (2022).

(1)R1 writes: “This is a fantastic study that has one major flaw: The authors have ignored extremely relevant literature prior research.” The reviewer goes on to note that it is “totally unacceptable” to not cite Thompson et al. (2022), as their article “developed a theory for why racial attitudes should be related to views about pit bulls and breed-specific legislation, it measured peoples’ perceptions of the racial composition of pit bull owners, it tested whether you could prime racial concerns and influence support for breed-specific legislation, and it also examined the relationship between racial attitudes and views about breed-specific legislation.”

RESPONSE: We first want to thank the reviewer for the kind words about our study. Second, we apologize for our failure to cite this important study. Not doing so was an honest omission that simply stemmed from us writing our initial draft of the manuscript long before that article was published. So, we’re very grateful that the reviewer brought these findings to our attention, and we’re pleased to highlight them prominently in our revised manuscript (more on that below).

(2) R1 relatedly writes, “True, the current submission is a MUCH better study than Thomspon et al. The former used a small sample, weaker measures, and focused only on college students. Still…the current authors need to cite Thompson et al. (2022), they need to discuss the findings in that study, and they need to explain how their study goes beyond it and offer some explanation for why the findings in it are different than the earlier ones.”

RESPONSE: We, once again, thank the reviewer for the nice words about our study and express sincere regrets over the omission of Thomspon et al. (2022) from our first submission.

We also really appreciate R1 pushing us to explain why the findings in our study may differ from theirs and now devote 1.5 paragraphs at the front-end of the manuscript to discussing these findings and offering informed explanations for why ours are different. After noting that there have been few empirical analyses testing scholarly and journalistic contentions about the racialization of pit bulls, the revised manuscript now states the following:

“Moreover, Thompson, Pickett, and Intravia’s (2022) recent empirical study found that neither experimentally linking pit bull owners with African Americans via racial imagery, nor harboring stereotypes of pit bull owners as disproportionately Black, were associated with support for breed-specific legislation among college students.

Thompson et al (2022), however, conclude that study by noting the need to replicate their findings with representative samples. They specifically discuss how the young age of their college sample could affect the results if attitudes toward pit bulls have improved since Michael Vick’s 2007 dog-fighting controversy. This is a particularly prescient point. Consistent with the unusually low levels of support for breed-specific bans in Thompson et al.’s data (1.74 on a 1-5 scale), we note multiple times throughout the manuscript that age is probably the strongest predictor of public opinion about pit bulls presumably because American youths have been socialized amidst increasingly positive images of the breed on social media. Younger and college-educated Americans score significantly lower in racial prejudice (see discussion below), as well, which could help further explain why the link between pit bulls and African Americans did not increase support for breed-specific legislation among college students.”

(3) R1 writes, “Given the current authors' focus on the perceived racial composition (or racial typification) of dog owners (e.g., Figure 2), I would also direct them, when talking about the racialization of crime (pp. 8-11), to the extensive work on how the racial typification of crime (i.e., the perceived racial composition of criminals) is related to support for harsh policies. The authors should start with Chiricos et al.'s (2004) seminal study and go from there in their literature review.”

RESPONSE: We regret the omission and acknowledge our embarrassing blind spot here as political scientists to some of the relevant literature in other disciplines. We are, therefore, grateful to the reviewer for alerting us to the relevant work on this topic in criminology. The Chiricos et al. piece on the racial typification of crime and support for punitive measures was particularly helpful and we now cite that study three different times in our revised manuscript. We also cite additional studies on the racialization of crime that we picked up from R1’s suggestion to look to the lit reviews in Chiricos et al. and Cullen et al. for guidance.

So, we want to conclude here by sincerely thanking the reviewer again for his help with these important additions to the revised manuscript.

Response to Reviewer 2

Thank you for both the kind words about our manuscript and for your thoughtful critiques of it. Your concerns about the automated sentiment analyses were particularly important in improving the revised manuscript.

(1) R2 writes, “I am fully persuaded by the analysis in the “Racial prejudice and public opinion” section. For one thing, I find it very hard to imagine that the relationship between racial and pit bull attitudes runs in the opposite direction. For another, I cannot think of any important omitted variable that isn’t quite closely related to something the authors already control for in some model…I think the authors could make more of the (many) reasons why we should take their correlational evidence very seriously.”

RESPONSE: We are SO very grateful to the reviewer for these comments. It is indeed difficult to imagine how these results would be susceptible to the same endogeneity issues found in the correlations between racial attitudes and support for affirmative action (Sniderman and Carmines 1997), welfare (Goren 2022), and Trump (Griffin et al. 2021). Nor is omitted variable bias a threat to the statistical significance of the findings. The relationship between racial attitudes and public opinion remained intact in the face of every model specification we tried, as there were only three consistent predictors of public opinion about pit bulls across the hundreds of regressions we’ve run--age, racial attitudes, and general favorability towards dogs--all of which are include in our multivariate analyses.

We were quite happy, then, to heed the reviewer’s advice and make more out of why we should take “the correlational evidence very seriously.” The concluding paragraph of this section in the revised manuscript now offers reasons why we’re confident that these relationships are not the product of endogeneity or omitted variable bias. The new discussion of omitted variable bias and the robustness of the findings across every model imaginable also indirectly addresses some of the concerns about model specifications raised by R3 (see below)

(2) R2 writes, “the analysis of coverage of pit bulls isn’t very convincing. It seems to me that the burden of this analysis is to show that coverage of pit bulls – and perhaps, by extension, wider cultural discourse concerning dogs – associates the breed with African Americans very prominently or regularly. But it’s only the very rare pit bull story that mentions African Americans, about 2%. I don’t know exactly how to calibrate this percentage, but it doesn’t sound very high to me. The authors need to provide some basis for thinking that this percentage indicates that associations between pit bulls and African Americans are sufficiently pervasive in the culture that we should expect views of pit bulls to be racialized.”

(3) R2 relatedly writes, “I don’t follow the authors’ analysis of dog-news sentiment. Figure 3 essentially depicts an interaction, with respect to tone, between the type of dog in a story and whether African Americans are mentioned. It seems to me that the observed interaction is the reverse of what we’d expect, under the authors’ argument. That is, if pit bulls were especially affected by association with African Americans, then I would expect the relative impact of that association on sentiment to be greater for pit bulls than for other dogs. But that’s not the case here: for non-pit bulls, association with African Americans increases the negativity of net sentiment by about 60%; for pit bulls, the comparable effect is about 40%.”

RESPONSE: These two passages above are both very fair critiques and it’s now clear to us from the reviews provided by R2 and R3 that the revised manuscript needed to overhaul how we present our automated content analyses.

To be sure, we still think the analyses in Figure 3 of the original manuscript are an important part of the story since racialized stories about pits are 20-points more negative than those that don’t explicitly reference African Americans and that there’s a larger total volume of negative racialized news stories about pit bulls than all the other dogs we looked at combined. We also think these numbers here are an enormous underestimation of negative racialized news coverage, as qualitative analyses suggest that negative associations between African Americans and pit bulls in media and pop culture occur largely through imagery--and our automated content analyses can only identify explicit references to race.

But we also completely agree with R2 and R3 that our automated content analyses just aren’t as convincing as the other quantitative analyses, and the evidence in support of H1 is not as strong as the data testing H2-H6 in the original manuscript. So, after careful consideration we decided to jettison the “Negative News Coverage” section from the revised manuscript.

Instead, the revision makes only brief reference to our “suggestive quantitative evidence” from Crimson Hexagon in the “Theoretical Background and Empirical Expectations” section. After discussing prior qualitative accounts of how media and pop-culture portraits negatively depict pit bulls when they’re linked up with African Americans in more detail than the original submission, the revised manuscript goes on to state:

"And our subsequent research provides some suggestive quantitative evidence on the heightened negativity of news coverage when pit bulls are associated with African Americans (McThomas and Tesler 2024). Drawing on automated sentiment analyses from Gary King’s analytics platform, Crimson Hexagon, we found that the net sentiment (positive minus negative) of headline news stories about pit bulls that explicitly mentioned African Americans was significantly lower (p<.001) than the already high levels of negativity in all news coverage of the breed (-68 to -48 respectively)."

We think that restructuring our discussion of media portraits this way has several benefits. First, and most importantly, deemphasizing the media findings leaves the manuscript less vulnerable to criticism since that was our weakest hypothesis test. Second, the media findings served largely to bolster empirical expectations about the link between racial attitudes and public opinion. Little is lost, then, from briefly referencing these automated content analyses in the theoretical background and empirical expectation section instead of dedicating a whole empirical section to them. Indeed, almost none of the article-length studies cited on how crime, welfare, and drug addiction have been racialized in public opinion via media portraits include original content analyses of news coverage. Third, referring the reader to the more detailed presentation of the automated content analyses from our book manuscript in progress, which includes an entire chapter on race and media portraits of pit bulls, allows us to address the critiques raised by the reviewers in much greater detail than we could do in the space allotted to a single section of an article. Finally, removing this section provides us with additional space to incorporate the reviewers’ other suggestions. The revised manuscript’s text (minus references) is nearly the exact same length as the original.

We are, therefore, most grateful to R2 and R3 for convincing us to do something we had been stubbornly reluctant to do even after receiving similar feedback from our colleagues. Upon closer reflection, we think there is a significant addition-by-subtraction effect here and that the manuscript is considerably strengthened by removing this material.

(4) R2 writes, “My other significant concern involves the experimental evidence. I accept that it supports the authors’ hypothesis (H5), but that hypothesis isn’t actually a very specific test of their argument. And other analysis of the experiment seems to threaten the authors’ interpretation of this effect in terms of racialization. Specifically, the inner-city treatment doesn’t increase the impact of racial attitudes (black favorability) on pit bull attitudes – and this is precisely the effect the authors need to establish, i.e., implicitly associating pit bulls with African Americans increases the weight of racial attitudes in pit bull attitudes.”

RESPONSE We appreciate this valid critique, especially since it also dovetails with some of R3’s comments below. The revised manuscript, therefore, takes multiple steps to address it.

First, we provide more reasons for why we do not think that the null interactive effect here for inner-city*Black favorability is a serious threat to interpreting the experiment in terms of racialization. In addition to our discussion of the prior studies showing that it’s a lot more difficult to experimentally prime racial attitudes in issues that are already racialized like pit bulls, we’ve incorporated R3’s comment into the revised manuscript about how interaction analyses are “extraordinarily power-hungry.” We now cite Andrew Gelman’s analysis, “You Need 16 Times the Size to Estimate an Interaction Than to Estimate a Main Effect” among others in that discussion and then use it as a segue to further highlight the significant interactive effect for inner-city*White. We think that significant interaction greatly aids the interpretation in terms of racialization, as it suggests that the inner-city treatment is tapping into something distinctly racial; we now explicitly say so in the revised manuscript.

At the same time, though, we’ve also added some additional caveats to conclude the experimental section, which reflect the legitimate concerns raised by both R2 and R3 (see more below). We think those qualifications help insulate the analysis a bit from critiques and are therefore grateful to both reviewers for their comments on this section.

(5) R2 includes some more minor comments, as well, such as our misnumbering of hypotheses and figures; the review also notes that the wording of H4 in the original manuscript (“stereotypes of Black men as violent will be particularly potent predictors of rating pit bulls unfavorable”) is vague with regards to what is meant by “particularly potent.”

RESPONSE: We thank the reviewer for identifying these smaller issues. The revised

Attachment

Submitted filename: plos memo.docx

pone.0305959.s003.docx (35.7KB, docx)

Decision Letter 1

Hans H Tung

2 Apr 2024

PONE-D-22-34733R1The Racialization of Pit Bulls: What Dogs Can Teach Us About Racial PoliticsPLOS ONE

Dear Dr. Tesler,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.Many thanks to your patience. We have been trying to collect enough quality reviews for reaching a reasonable decision about your manuscript. While most reviewers have decided to accept the revised manuscript as it stands now, one of them actually made a fairly critical comment on the necessity for this paper to have a more extensive section on data and methods. Despite the other strengths of the current version of the manuscript, we still find it imperative for the paper to fully address the concern raised by this reviewer (#4).  

Please submit your revised manuscript by May 17 2024 11:59PM. We will then quickly make our final decision.  If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Hans H. Tung

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #4: (No Response)

Reviewer #5: (No Response)

Reviewer #6: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #4: No

Reviewer #5: Yes

Reviewer #6: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #4: No

Reviewer #5: I Don't Know

Reviewer #6: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors did a phenomenal job revising their manuscript. This is an impressive study that makes an important contribution to the literature. It also is now situated well within the relevant interdisciplinary literature.

Reviewer #2: The authors have done a great job of responding to my concerns and those of the other reviewers. As a result, an already very strong paper is just that much stronger. I have no further revisions or other suggestions to make.

I should note that I understand the authors’ reluctance to exclude the media analysis from the paper, and I agree that the large negative effect of racializing content on the tone of pit bull stories is indicative. I’m glad to hear this content will find a home in the book manuscript.

Reviewer #4: The investigators may have engaged with the relevant literature. However, the synthesis and statistical presentation of the information is awkward and, in places, difficult to follow. For example, in the abstract they list 5 points which they believe they demonstrate. However, not until later in the manuscript do they start addressing what appears to be the five hypothesis, H1 to H5, which this reader assumes are the major goals of the paper. They should have been formerly stated as hypotheses or at least the opposite or alternatives of five null hypotheses at the start of a formal statistical analysis plan. The paper is primarily a descriptive conclusion by the investigators after literature or survey gathering. There is no description of a systematic review of the information gathered and formal planned statistical synthesis of the information. The authors merely pull information from their gathering and then reach the conclusion of a racial bias. One possibility would be a good statistical meta-analysis of the information which would apply to this data with a rigorous statistical conclusion. Also a meta regression would probably point out any possible causes of heterogeneity in the results. The presentation, as it exists, is fragmented.

In addition, there appears to be some relevant information. For example Figure 1 is presented with percentages which is fine. However, as mentioned above, the authors give their take on the results descriptively. In the last bar presentation ‘Rate pit bulls very favorably’ how significant is that two percentage point difference. Probably statistically so with the sample size, but how meaningful practically is that difference?

On page 8 below Figure 2, the authors note that, “It’s hardly a coincidence, either, that the two dog breeds stereotyped as Black-owned are the two breeds that evoke the most fear by far from the public (Tesler 2020).” Has fear and type of breed been statistically associated in the reference? That p-value should be noted. Also throughout the manuscript the words, ‘suggest’ and ‘implicit’, appear which gives the impression of possible author bias, which I’m sure is not the case. See page 22,” The results in Figure 4 show that implicitly associating African Americans with pit bulls via the “inner city” treatment also significantly decreased white Americans’ support for legalizing the breed.” See page 22 to 23, “ The highly significant negative interaction here between inner city white dovetails with prior experimental research showing that implicit race associations like inner-city are more potent in public opinion for whites than Black Americans (White 2007); and it suggests that our intended racialization experiment is tapping into something distinctly racial.” These are not strong statistical arguments.

Some clarity is needed throughout. On Figure 3 what is the reason for some of the interaction across these two surveys. On Table A3 “Old fashion Racism” is a variable. How strongly does that really associate with choosing a dog? There are no measures of concordance given with the logistic presentations. So the strength of the association is not clear. Like wise on Table 1, where are the R-square or partial r-square measures? This brings up a point brought up earlier of missing information. Would it be helpful to have Black American opinions for the information on Table 1?

The paper needs a thorough rewrite showing what can be said definitively and statistically and not necessarily implicit or suggested. Also as a previous reviewer pointed out, how representative of the population is this information? Some demographic descriptions of this sample may be helpful.

Reviewer #5: (No Response)

Reviewer #6: The topic is wonderful, creative, and necessary. However, there are several problems. For example, APA style guidelines are not followed, and conventions of standard American academic English are only erratically shown (e.g., lots of writing in second-person voice; use of contractions; basic grammar errors, such as problems with capitalization).

I would recommend that you talk with a skilled editor who is familiar with both grammar and the conventions of APA style, 7th edition. The writing style is disjointed and difficult to read; the connections among subtopics seems loose at best. Again, while the topic is of critical importance, literature needs to be better used so that it can support the good points that the authors are otherwise trying to make.

I would be happy to elaborate further in a conversation, if that is permitted. There is a lot of room here to create an outstanding, excellent, and transformative article.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: J. Scott Matthews

Reviewer #4: No

Reviewer #5: No

Reviewer #6: Yes: Adam Duberstein

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Jun 28;19(6):e0305959. doi: 10.1371/journal.pone.0305959.r004

Author response to Decision Letter 1


30 Apr 2024

Response to the Editor

Thank you for the opportunity to revise and resubmit the manuscript. We are especially appreciative that you plan to make a quick decision upon receipt of the revised manuscript without another round of reviews.

We were also particularly pleased to see that R1 and R2 described our response to their critiques as “phenomenal” and “great” respectively, and that R6 described the topic as “wonderful, creative, and necessary.”

As the memo details, we have restructured the revised manuscript in accordance with your suggestion to have a new section that provides greater detail up front on the data and methods used to test our hypotheses. While we were initially reluctant to make this change, we think it has improved the manuscript and hope that these revisions, combined with the other reviewers’ evaluations, have now made the article suitable for publication in PLOS ONE.

Response to Reviewer 4

We thank the reviewer for pushing us to provide a more detailed standalone section on the data and methods used in our manuscript. Doing so helped strengthen the revised article.

(1) R4 first writes, “in the abstract they list 5 points which they believe they demonstrate. However, not until later in the manuscript do they start addressing what appears to be the five hypothesis, H1 to H5, which this reader assumes are the major goals of the paper. They should have been formerly stated as hypotheses or at least the opposite or alternatives of five null hypotheses at the start of a formal statistical analysis plan.”

While our five theoretically informed hypotheses were all formally stated in the “Theoretical Background and Empirical Expectations” section of the prior manuscript, it is certainly reasonable for the reviewer to ask for a more detailed standalone section on the data and methods used to test those expectations.

The revised manuscript, therefore, now includes a new “Data and Methods” section following the section on “Theoretical Background and Empirical Expectations.” This new section details the various data, measures, and statistical analyses used to test our formal hypotheses. We think that these revisions have improved the manuscript and thank both the reviewer and the editor for pushing us to make them.

(2) In addition, R4 writes, “there appears to be some relevant information [missing]. For example Figure 1 is presented with percentages which is fine. However, as mentioned above, the authors give their take on the results descriptively. In the last bar presentation ‘Rate pit bulls very favorably’ how significant is that two percentage point difference. Probably statistically so with the sample size, but how meaningful practically is that difference?”

We’d like to respectfully note here that the statistical and substantive significance of this difference were addressed on pg 6-7 of the prior manuscript where we write: "There were not significant differences between the races in how favorably they rated pit bulls; but after controlling for the fact that white people have more favorable views about dogs than Black people do, and that attitudes about dogs in general strongly predict attitudes towards pit bulls (see Table 1), African Americans were significantly more likely than whites to rate pit bulls very favorably (40% to 31% respectively)."

(3) On page 8 below Figure 2, R4 writes, “the authors note that, ‘It’s hardly a coincidence, either, that the two dog breeds stereotyped as Black-owned are the two breeds that evoke the most fear by far from the public (Tesler 2020).” Has fear and type of breed been statistically associated in the reference?’

The reviewer asks a very fair question here. So, the revised manuscript now elaborates on this point by adding the following information on pg. 8 about the link between fear and breed provided in this reference:

“Over 40 percent of respondents in a 2018 Lucid survey we conducted said that “scary” described pit bulls and rottweilers ‘extremely’ or ‘very well’ (46 and 41 percent, respectively). But only about 10 percent said the same thing about golden retrievers, collies, Dalmatians and Labradors. These four breeds were all rated at least 15 percentage points more favorably than rottweilers and pit bulls in our surveys as well (Tesler 2020).”

(4) R4 further writes, "Also throughout the manuscript the words, ‘suggest’ and ‘implicit’ appear, which gives the impression of possible author bias, which I’m sure is not the case. See page 22, “The results in Figure 4 show that implicitly associating African Americans with pit bulls via the “inner city” treatment also significantly decreased white Americans’ support for legalizing the breed.”

We were a bit perplexed by this comment, as our repeated use of “implicit” simply refers to the long line of social science literature cited in the article on the impact of messages that indirectly associate a racial group with a policy/person/dog with racially evocative words (e.g. inner-city) without making an explicit reference to that group by name.

To avoid any potential confusions about the meaning of “implicit” here, we now make further note of this distinction between implicit vs. explicit racial references on pg 13, writing, “Several experiments, which randomly assigned subjects to receive implicit racialized messages (e.g., racial images and/or race-coded language that doesn’t explicitly reference a particular racial group) about specific issues, have affected white Americans’ opinion about crime, welfare, drug treatment, gun control, government spending, education programs, Social Security, the minimum wage, the Iraq War, and the coronavirus pandemic.”

(5) R4 writes, “On Table A3 “Old fashion Racism” is a variable. How strongly does that really associate with choosing a dog? There are no measures of concordance given with the logistic presentations. So the strength of the association is not clear. Like wise [sic] on Table 1, where are the R-square or partial r-square measures?

These are fair questions that we thank the reviewer for raising. The revised manuscript therefore includes R-squared or Pseudo R-squared measures in our regression tables.

Attachment

Submitted filename: plos memo2.docx

pone.0305959.s004.docx (17.4KB, docx)

Decision Letter 2

Hans H Tung

10 Jun 2024

The Racialization of Pit Bulls: What Dogs Can Teach Us About Racial Politics

PONE-D-22-34733R2

Dear Dr. Tesler,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Hans H. Tung

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Hans H Tung

21 Jun 2024

PONE-D-22-34733R2

PLOS ONE

Dear Dr. Tesler,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Hans H. Tung

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Appendix

    (DOCX)

    pone.0305959.s001.docx (61.7KB, docx)
    S1 File

    (ZIP)

    pone.0305959.s002.zip (5.8MB, zip)
    Attachment

    Submitted filename: plos memo.docx

    pone.0305959.s003.docx (35.7KB, docx)
    Attachment

    Submitted filename: plos memo2.docx

    pone.0305959.s004.docx (17.4KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting information files.


    Articles from PLOS ONE are provided here courtesy of PLOS

    RESOURCES