COVID-19 and the Gender Employment Gap among Parents of Young Children

Abstract

Working life in Canada has changed dramatically during the COVID-19 pandemic. Using Labour Force Survey data, we show that gender employment gaps among parents of young children widened considerably between February and May 2020, net of differences in job and personal characteristics. Gender gaps grew more for parents of elementary school-aged children rather than preschoolers, and among less educated parents. To aid postpandemic recovery and prepare for future disruptive disasters/pandemics, policy-makers should focus attention on fostering an accessible, well-funded public care sector and implementing flexible leave policies beyond the period of infancy to help working parents manage caregiving demands equitably.

Introduction

Since the World Health Organization declared COVID-19 as a pandemic on 11 March 2020, working life in Canada has changed dramatically. As governments took drastic measures to reduce the spread of COVID-19, many workplaces were forced to close, while others moved as much work as possible online. Employment levels plummeted (Lemieux et al. 2020). For parents of children who were too young to be left unsupervised, the pandemic created additional challenges as schools and childcare centres were closed. Parents able to work from home struggled to juggle childcare and employment duties, whereas others faced stark choices between continuing to go to work and caring for children. For single parents, maintaining both employment and caregiving is a particular challenge. For couples, managing life in the pandemic has meant difficult choices about who cares, who works, and how.

Given extant gender inequalities in the division of paid work and care work, and in parents’ employment experiences (Beaujot, Liu, and Ravanera 2017; Fuller 2018; Fuller and Cooke 2018; Guppy, Sakumoto, and Wilkes 2019; Moyser 2017), understanding how the pandemic has impacted gendered inequalities among parents is of critical importance. The pervasive nature of COVID-19 has led some to characterize the pandemic as a “great equalizer.” This metaphor portrays the pandemic as an exogenous shock that limits the economic activity of almost everyone, regardless of social location (Jones and Jones 2020). Emerging evidence, however, challenges this view. It shows that the pandemic is exacerbating pre-existing social inequalities by more strongly impacting women (at least initially), less-educated and lower-wage workers, and other groups that face disadvantage in the labour market (Beland et al. 2020; Kochhar and Barroso 2020; Kristal and Yaish 2020; Lemieux et al. 2020; Qian and Fan 2020). We expect gender inequality to grow among parents of younger children as mothers take on a disproportionate share of childcare, especially among workers who tend to be positioned at the bottom of the labour market.

Overall gender differences in the impact of the pandemic stem, in part, from pervasive gender segregation in the workplace. As female-dominated in-person service jobs (e.g., restaurant, hotel, and childcare jobs) have been among the hardest hit amid lockdowns, the gender impacts of the pandemic on employment are unequal (Kochhar and Barroso 2020; Lemieux et al. 2020). Insofar as education strongly impacts one’s labour market position and occupational gender segregation is higher among less educated workers (England 2010), these gender effects may also vary across educational groups. Although gender segregation across occupations and industries will contribute to unequal effects regardless of parental status, mothers and fathers face additional constraints that have the potential to magnify these effects. Even if their jobs remain available, parents may be unable to work without schools and childcare centres. Whether employed parents share care work equitably or default to a female caregiver model will have potentially long-lasting repercussions for gender equity as the pandemic ultimately recedes.

The more marginal economic position of mothers versus fathers, such as their greater likelihood of working part-time and in low-wage firms (Cooke and Fuller 2018; Fuller 2018; Moyser 2017), suggests that mothers likely bear the brunt of caregiving and hence employment losses. Even absent economic incentive structures, deeply entrenched gender norms about who is best suited to caring for children push mothers to the fore as caregivers. Preliminary analysis finds that mothers’ employment has been more strongly affected by the pandemic than that of fathers in Canada (Statistics Canada 2020). In this research brief we delve more deeply into how the pandemic affects gender inequality among parents. Drawing on Labour Force Survey data covering February to May 2020, we examine trends in the gender gap in employment among parents in the wake of the pandemic. We focus on the group with the greatest childcare responsibilities, parents with a youngest child aged 0–12 years, limiting our analysis to those already attached to the labour market (employed or having been employed in the past year) when the pandemic hit. To provide further nuance, we disaggregate results by educational attainment and assess both gross patterns and patterns net of differences in job and demographic characteristics.

Data

We use data from the public use microdata files of Statistics Canada’s Labour Force Survey (LFS).¹ The LFS is a monthly household survey with a rotating panel design and when weighted, it provides nationally representative data on the Canadian working-age population (with the exclusion of indigenous people living on reserves, residents of institutions, full-time members of the Armed Forces, and a small number of people living in very remote areas).

We pooled the monthly data from February to May 2020 to examine the gender gap in employment immediately before and also during the COVID-19 pandemic (n = 744,654). We limit our analysis to respondents already attached to the labour market at the beginning of the pandemic—those who were employed and those who were not currently employed but worked within the last year (n = 497,188). We further restrict our sample to respondents aged 25 to 54 (those in their prime working years; n = 300,226). Given our focus on parents of children who are too young to be left without supervision, we limit our sample to parents whose youngest child was between the ages of 0 and 12 years at the time of the survey. We further subdivide our analysis between those whose youngest child was under 6 (n = 60,402) and those whose youngest child was between 6 and 12 (n = 51,630). Children in the latter age group, while still requiring care and supervision, typically have more capacity to occupy themselves and may therefore create less of a challenge for parents able to work from home. After observations with missing values on the variables used in the analysis are excluded, our final analytic sample includes 60,364 parents with a youngest child under 6 and 51,600 parents with a youngest child aged 6–12 years.

Variables

Our main dependent variable is an indicator of currently being employed (1 = employed; 0 = otherwise). This includes those who did any work for pay or profit during the reference week or who had a job but were absent from work (Statistics Canada 2018). Focusing on employment rather than unemployment is preferable, inasmuch as widespread workforce closures mean that most of those who lost their jobs would be unable to search meaningfully for new employment (and hence be counted as unemployed) in the initial months of the pandemic. Workers who need to find new jobs during or in the aftermath of a pandemic are most at risk of ongoing economic insecurity and career disruption—layoffs can have negative earnings effects well beyond the short term (Brand 2015; Morissette, Qiu, and Chan 2013). This employment measure thus provides the best hint of potential longer-term gendered effects. At the same time, those who remain employed but are absent from work may also be disadvantaged. Some workers may have been (re)employed but remained absent from work when the government implemented a 75% wage subsidy for employers whose business was affected by COVID-19 at the end of March. Such workers effectively experienced a 25% wage cut. Others received no wages at all if their employers chose not to avail themselves of this program, relying instead on the Canada Emergency Response Benefit (CERB), which does not fully replace lost earnings for higher-income workers. Further, if their absence is not due to the employer shutting down operations but because of their need to provide childcare, they risk being seen as most expendable if their employer subsequently needs to lay off workers. We therefore also examine an indicator of currently being employed and at work (= 1; 0 = otherwise) as a secondary dependent variable.

Our main independent variables are survey month (February, March, April, May) and the respondent’s gender (men, women), parental status (youngest child under 6 and youngest child aged 6–12), and educational attainment (high school or less, postsecondary credential, and university degree or above).

We control for a series of job attributes and the respondent’s basic demographic characteristics (Schirle 2015): dummy variables for 40 occupational categories, 21 industry categories, full-time or part-time status, and class of worker (public sector, private sector, self-employed). We also include a continuous variable to measure job tenure with employer (in months). Note that for employed respondents, we measure the attributes of their current job, whereas for respondents who were not currently employed, we measure the attributes of their last job. For individuals’ characteristics, we include dummy variables for age groups (25–29, 30–34, 35–39, 40–44, 45–49, 50–54), marital status (married/common-law, previously married, never married), and immigration status (immigrant who landed within the previous 10 years, immigrant who landed more than 10 years earlier, and non-immigrant). We also include a series of province indicators. Appendix Table A.1 presents weighted descriptive statistics for the variables.

Analytic Strategies

We use logistic regression models to assess how the gender gap in employment changed between February and May, 2020. We first run models with the interactions between gender and survey month only, separately for parents with a youngest child under 6 and parents with a youngest child aged 6–12. Next, we add control variables to see whether fathers’ and mothers’ job attributes and demographic characteristics account for the gender gap in employment. In addition, we run models without and with control variables by parental status and educational attainment, to assess class differences in the gender employment gap. All analyses are weighted. To facilitate interpretation, we convert results to percentage point differences in men and women’s predicted probability of employment and present these marginal effects graphically (Mize, Doan, and Long 2019).

Results

In Figure 1, we show the gender difference in employment by survey month and parental status. Results from models without controls are in red (black in print version), and results from models with controls are in blue (grey in print version), with 95% confidence intervals shown as well. Among parents whose youngest child was under 6, there was a small gender employment gap of one percentage point in February (p = 0.018; recall that our sample only includes respondents employed within the past year, so we are selecting on those already attached to the labour market). This gender gap increased to 3.8 percentage points in March (p < 0.001). Interestingly, the gap shrank to almost zero in April, to the point where there was no significant gender difference (p = 0.379). This pattern is consistent with the finding from Statistics Canada (2020) that women accounted for a disproportionate share of job losses in March, but in April employment losses were larger among men. Gender parity shown in April was short-lived, however. As the Canadian economy started to open back up in May, men regained more of their employment losses than women (Statistics Canada 2020). Similarly, the gender employment gap among parents of pre-school-aged children grew again, reaching 2.5 percentage points (p = 0.002) and ending up significantly greater than the gap in February (p < 0.05). Controlling for job and demographic characteristics has little impact on results, suggesting that, among parents of young children, the growing gap cannot be attributed simply to differences in the types of jobs mothers and fathers hold or their personal characteristics.

Figure 1:

Gender Gap in Employment (Percentage Points), by Survey Month and Age of Youngest Child, without and with Controls

Among parents whose youngest child was aged 6–12, there was an even stronger and more consistent growth in the gender employment gap. Specifically, women’s disadvantage in probability of employment was 0.8 percentage points in February (p = 0.05), 4.4 percentage points in March (p < 0.001), 5.5 percentage points in April (p < 0.001), and 7.3 percentage points in May (p < 0.001). Significance tests indicate that the gender employment gap during the pandemic (from March through May) was significantly larger than that prior to the pandemic (in February). After we control for a host of covariates, the gender gap in employment narrows but is still significantly larger in March through May than in February (2.5, 2.3, and 4.2 percentage points in March, April, May, respectively, versus essentially zero in February).

Aggregate patterns can hide substantial intragroup variability. Recent research shows that the negative impact of the pandemic on employment is more pronounced among less educated workers in Canada (Béland et al. 2020) and working remotely is less of an option for less educated workers to juggle work and family (Gallacher and Hossain 2020; Messacar, Morissette, and Deng 2020). Given the vulnerable labour market position of the less educated workers and the fewer institutional resources that they can draw on to balance work and family, an important question arises: Does the gender gap in employment vary by class (indicated by educational attainment)? In Figure 2, we present the gender gap in the probability of being employed by survey month and educational attainment among parents with a youngest child under 6. Figure 3 presents the parallel results for parents with a youngest child aged 6–12.

Figure 2:

Gender Gap in Employment (Percentage Points), by Survey Month and Educational Attainment, without and with Controls, Parents with Youngest Child under 6 y

Figure 3:

Gender Gap in Employment (Percentage Points), by Survey Month and Educational Attainment, without and with Controls, Parents with Youngest Child Aged 6–12 y

As shown in Figure 2, the gender employment gap among parents with a child under 6 widened much more during the pandemic among the less educated. Among those with a high school education or less, women’s probability of being employed lagged behind men’s by 2.5 percentage points in February (p = 0.052), with the gap increasing to 5.6 percentage points in March (p = 0.001), to 5.1 percentage points in April (p = 0.013), and further to 11.5 percentage points in May (p < 0.001). In fact, the gender employment gap in May was significantly larger than the gap in the previous three months (p < 0.05). Similar patterns appear among those with a postsecondary credential, with the gender employment gap (in percentage points) increasing from 2.8 in February (p < 0.001) to 4.4 in March (p < 0.001), and further to 6.0 in May (p < 0.001; the gap was smallest in April [1.8, p = 0.183]). Again, the gender gap in employment was significantly larger in May than in February and April (p < 0.05). In contrast, among those with a university degree or above, the gender employment gap was only present in March (3.6 percentage points; p < 0.001) but it was not significantly different from zero in the other three months (p > 0.05). Thus, for university-educated parents with young children, women were more negatively affected in March when the pandemic first hit Canada and workplaces, schools, and childcare centres started to close, but this disparity was short-lived. By April, there was no longer a gender employment gap among highly educated parents who were already attached to the labour market when the pandemic hit.

After we control for a variety of covariates, gender employment gaps remain for most groups. We do notice that controlling for covariates explains much of the gender employment gap among the least educated parents with pre-school-aged children, especially in March and April, when social distancing measures were most strictly enacted. In supplementary analysis, we decomposed the role of each job attribute measure in the model and found that full-time/part-time status and occupation played the most important role. This suggests that greater gender occupational segregation and the disproportionate share of mothers with young children (relative to fathers) working part-time among the working class contribute strongly to the more pronounced gendered effects of the pandemic in this group.

Figure 3 shows that the widening gender employment gap in the wake of the pandemic among parents with school-aged children was also more pronounced among the least educated. Among those with a high school education or less, the gender employment gap widened more than 10 times between February and May (from 1.6 percentage points in February to 16.8 percentage points in May; the difference of 15.2 percentage points is statistically significant). Adding controls explains the gender gap in March and April, but not in May, suggesting that the pandemic may have a lasting impact on gendered employment patterns among the least educated parents. Similarly, among moderately educated parents with school-aged children, the gender employment gap widened over time almost in a linear fashion, but the temporal trend was much less pronounced than that among the least educated parents. Specifically, among parents who had a postsecondary credential and a youngest child aged 6–12, the gender employment gap increased from 1.2 percentage points in February (p = 0.094) to 4.9 percentage points in March (p < 0.001) and 5.9 percentage points in April (p < 0.001), and further to 7.5 percentage points in May (p < 0.001). Notably, adding controls explains almost all of the gender employment gap. As with parents of younger children, the gender employment gap among parents of school-aged children was affected the least for the most educated group, the group with a university degree or above. However, it did still widen significantly from a non-significant difference of 0.7 percentage points in February to about 4 percentage points in March through May. Adding controls explains little of this increase.

So far, we have considered patterns of employment regardless of whether people were actually at work or absent. While providing the best measure of economic security, this measure misses gendered patterns of leave-taking to manage caregiving. If we look at people who were employed and at work, does our result change? Figure 4 reveals that among parents with pre-school-aged children, the gender gap in being employed and at work was already present in February across educational groups. This gender gap widened during the pandemic, again more so for the less educated. Adding controls does not change the gendered employment impacts of the pandemic. As shown in Figure 5, the class difference is particularly striking among parents with school-aged children: The gender gap in the probability of being employed and at work increased in a linear manner with the survey month among those with a high school education or less. In contrast, among university-educated parents of school-aged children, women lagged significantly behind men in being employed and at work in March, but the gender gap narrowed in April and resumed almost to prepandemic levels in May.

Figure 4:

Gender Gap in Being Employed and at Work (Percentage Points) by Survey Month and Educational Attainment, without and with Controls, Parents with Youngest Child under 6 y

Figure 5:

Gender Gap in Being Employed and at Work (Percentage Points), by Survey Month and Educational Attainment, without and with Controls, Parents with Youngest Child Aged 6–12 y

Taken together, our results suggest that the pandemic has exacerbated gender inequalities among parents, especially among parents of school-aged children. Not all educational groups bear the gendered burden equally. Our results show that the employment of mothers with a high school education or less was hit much harder than that of their male counterparts, and less educated women’s greater disadvantage in employment relative to men widened further in May when the Canadian economy started to open up. By contrast, the employment impact of the pandemic is more equally distributed between highly educated men and women and does not seem to last.²

Discussion and Conclusion

Adding to the nascent literature on the impact of COVID-19 on gender inequalities (Kochhar and Barroso 2020; Kristal and Yaish 2020), we find that far from being a greater equalizer, the COVID-19 pandemic is in fact exacerbating preexisting inequalities. Among parents of children too young to be left unsupervised, mothers’ employment is hit harder by the COVID-19 pandemic than that of fathers, widening the gender employment gap among parents.³

Mothers’ concentration in occupations most at risk of job loss and their much higher likelihood of working part-time play a substantial role in explaining the growing gender employment gap among parents of young children. As the Canadian economy starts to open up and service sector jobs return, the gender gap may diminish. Much depends, however, on the availability of care arrangements. Governments have started allowing previously closed childcare centres and schools to reopen, and some summer camp options for school-aged children are becoming available. However, restrictions on capacity and operating procedures threaten the ongoing financial viability of childcare centres, and parents’ concerns for safety may also make them hesitant to enroll their children. Childcare centres report considerable uncertainty about their ability to reopen while maintaining both safety and financial viability (Friendly, Forer, and Vickerson 2020). Whether there will be enough spaces for children who need them without greater government support is thus an open question. To the extent that jobs return but care options remain limited, the gender gap in employment will likely continue to grow rather than diminish.

The finding that the gender employment gap increased most among parents of school-aged children (rather than pre-school-aged children) highlights the importance of care provisions for this demographic. Public policy, to the extent that it has engaged with childcare provision, has focused most heavily on pre-school-aged children (see, e.g., Canada 2017; Stalker and Ornstein 2013). And, indeed, having children is typically more of an impediment to mothers’ employment when children are young. As children reach school age, the gender gap in labour force participation among parents wanes, in line with public attitudes that are more supportive of maternal employment for mothers of older children (Antonini et al. forthcoming). A growing gender employment gap among parents of elementary-school-aged children in the wake of the pandemic threatens this pattern. In the short term, ensuring the viability of the summer-care sector will thus be critical if we are to avoid long-lasting exacerbation of gender inequality. Looking forward, it will also be important to recognize the mismatch between school and work schedules and ensure that after-school programs and summer care are included in policy initiatives around childcare.

The greater impact of COVID-19 on gender inequality among less educated parents may also grow rather than recede with time. We find that gendered labour market effects of the pandemic are distributed unevenly across social classes. The gendered impact of the pandemic on parental employment is especially pronounced among parents with a high school education or lower. In contrast, for parents with at least a university degree, a more negative impact of the pandemic on mothers’ employment was briefly seen in March, but the gender employment gap recovered quickly to a level similar to the prepandemic gap. Our research highlights the double jeopardy faced by less educated mothers of young children in the wake of the pandemic, given the childcare responsibilities, fewer economic resources, and vulnerable labour market positions borne by these women. There is the potential for the COVID-19 pandemic to have a lasting impact on gendered employment patterns among the less educated, which may further put working-class women in particularly disadvantaged positions in the labour market. Our research thus underscores the urgency of government support for the care sector in the wake of the pandemic, which has been “confusing, uneven, and often less than adequate” (Friendly et al. 2020). More than ever, it is apparent that childcare is an essential service, and must be funded and organized to ensure accessibility and affordability for all who need it.

The pandemic also underscores limitations in leave provision in Canada. Most provinces and the federal jurisdiction have enacted and/or extended job-protected leaves in employment standards for those caring for family members in the pandemic, although particular entitlements vary. These provisions are, however, temporary. If job protections for caregiving are rescinded before childcare is fully available, mothers’ employment will take a further hit. Outside COVID-19-specific measures, leave provisions for caregiving are limited once children are older than 18 months. Legal prohibitions against family status discrimination may provide some protection to parents, but ambiguities around what constitutes “reasonable accommodation” for caregiving make this by no means assured (Hirsh and Fuller forthcoming). More generous and flexible leave provisions that allow some portion of parental leave to be taken when children are older would better serve the diverse parenting demands in today’s society. Even outside the complete closure of schools and childcare centres, the ability to take some time to care for children without penalty would help parents better manage the sometimes unpredictable demands of parenting without the fear of losing their jobs. This is especially important for less educated parents, who disproportionately work in on-site jobs without flexible schedules (Fuller and Hirsh 2019).

The implications of leave provisions need to be considered carefully along gender and class lines. There is a danger that more generous leave provisions may exacerbate gender inequality in labour markets if they are used by mothers more than fathers (Brady, Blome, and Kmec 2018; Budig, Misra, and Boeckmann 2016; Mari and Cutuli 2018). To reduce the chance of job loss and the amount of time away from work that mothers have to bear due to childcare responsibilities, any expansion of leave policies should be accompanied by mechanisms ensuring that they promote men’s participation in care. In tackling this challenge, policy-makers also need to be cognizant that gendered pressures can vary for differently situated families. In practice, it may be easier for more affluent families to share the work of earning and caring during the pandemic, given the characteristics of their work and their greater financial resources. Sharing leave between parents can create greater financial hardships if their earnings are low and unequal, especially when income supplements do not fully offset lost wages (McKay, Mathieu, and Doucet 2016).

Our research is not without limitations. In particular, we have only examined employment, but not work hours. To the extent that mothers are also more likely than fathers to scale back work, our results likely underestimate the gendered impacts of the pandemic on labour market outcomes. In addition, given data limitations, we can only analyze patterns at the level of the individual. Couple-level data, which are not currently made available in the LFS public-use files, would be especially welcome to examine how couples actually bargain and negotiate work–family arrangements. Finally, we encourage additional work on the particular circumstances of single parents. Employment among lone mothers has increased substantially in recent decades, although it still lags that of mothers in couples (Beaujot, Du, and Ravanera 2013; Uppal 2015). Understanding the impact of the pandemic on the employment of lone mothers is of critical importance.

The COVID-19 pandemic has brought deep-seated and persistent inequalities to the fore. Health and social risks have been uneven across groups. Our analysis of employment gaps has highlighted the intersectional inequalities disproportionately borne by less educated mothers. The gendered and class-based inequalities in employment exacerbated by the pandemic will not automatically disappear when the economy opens up. Unequal employment losses risk further entrenching disadvantage. Thus, concerted policy attention will be necessary to help mothers, especially those with less education, return to the labour market. To aid equitable postpandemic recovery and prepare for future disruptive crises, policy-makers should focus attention on creating a robust and well-funded public care sector and implementing more flexible leave policies that allow fathers and mothers at various parenting stages to manage caregiving demands when needed.

Appendix

Table A.1:

Descriptive Statistics, by Age of Youngest Child and Gender

Variables	Mean or %
	Parents with youngest child under 6		Parents with youngest child aged 6–12
	Men	Women	Men	Women
Employed	89.91%	87.85%	92.19%	87.62%
Employed, at work	78.72%	59.32%	80.72%	72.47%
Survey month
February	24.41%	24.12%	24.65%	24.34%
March	25.36%	25.50%	25.10%	24.85%
April	25.00%	25.22%	24.80%	24.84%
May	25.23%	25.16%	25.44%	25.97%
Highest educational attainment
High school or less	23.93%	15.01%	24.39%	18.93%
Postsecondary credential	38.47%	35.54%	37.64%	36.32%
University degree	37.60%	49.45%	37.96%	44.75%
Occupation
Senior management occupations	0.29%	0.09%	0.55%	0.30%
Specialized middle management occupations	3.73%	3.00%	4.79%	4.64%
Middle management occupations in retail and wholesale trade and customer services	2.66%	2.13%	3.85%	2.16%
Middle management occupations in trades, transportation, production, and utilities	5.22%	0.95%	5.55%	1.45%
Professional occupations in business and finance	4.71%	7.63%	4.98%	6.04%
Administrative and financial supervisors and administrative occupations	2.48%	8.46%	2.62%	8.76%
Finance, insurance, and related business administrative occupations	0.54%	1.92%	0.83%	2.02%
Office support occupations	0.72%	5.73%	0.63%	5.71%
Distribution, tracking, and scheduling coordination occupations	1.43%	0.98%	1.95%	1.17%
Professional occupations in natural and applied sciences	10.81%	4.01%	8.89%	2.82%
Technical occupations related to natural and applied sciences	5.61%	1.83%	4.67%	1.52%
Professional occupations in nursing	0.49%	4.76%	0.71%	3.18%
Professional occupations in health (except nursing)	1.89%	3.36%	2.33%	3.00%
Technical occupations in health	1.16%	5.53%	0.72%	3.99%
Assisting occupations in support of health services	0.40%	3.34%	0.34%	3.54%
Professional occupations in education services	2.76%	9.03%	3.81%	8.99%
Professional occupations in law and social, community, and government services	1.92%	5.42%	1.96%	4.36%
Paraprofessional occupations in legal, social, community, and education services	0.48%	5.67%	0.46%	5.55%
Occupations in front-line public protection services	1.57%	0.28%	1.81%	0.64%
Care providers and educational, legal, and public protection support occupations	0.41%	1.98%	0.33%	3.30%
Professional occupations in art and culture	0.62%	1.00%	0.72%	0.71%
Technical occupations in art, culture, recreation, and sport	1.28%	1.83%	0.95%	1.47%
Retail sales supervisors and specialized sales occupations	3.72%	3.34%	3.93%	3.47%
Service supervisors and specialized service occupations	2.00%	2.74%	2.53%	3.06%
Sales representatives and salespersons—wholesale and retail trade	2.93%	2.20%	2.82%	2.53%
Service representatives and other customer and personal services occupations	1.78%	4.51%	1.56%	4.49%
Sales support occupations	0.60%	1.65%	0.46%	1.96%
Service support and other service occupations, n.e.c.a	2.03%	2.78%	1.97%	3.53%
Industrial, electrical, and construction trades	11.68%	0.41%	9.87%	0.56%
Maintenance and equipment operation trades	6.13%	0.21%	6.56%	0.26%
Other installers, repairers, and servicers and material handlers	1.59%	0.41%	1.80%	0.50%
Transport and heavy equipment operation and related maintenance occupations	6.43%	0.39%	5.91%	0.81%
Trades helpers, construction labourers, and related occupations	1.37%	0.03%	0.99%	0.14%
Supervisors and technical occupations in natural resources, agriculture, and related production	1.93%	0.34%	1.56%	0.31%
Workers in natural resources, agriculture, and related production	0.93%	0.28%	0.64%	0.46%
Harvesting, landscaping, and natural resources labourers	0.54%	0.21%	0.41%	0.14%
Processing, manufacturing, and utilities supervisors and central control operators	1.51%	0.22%	2.02%	0.27%
Processing and manufacturing machine operators and related production workers	1.85%	0.77%	2.01%	1.11%
Assemblers in manufacturing	1.11%	0.27%	1.01%	0.42%
Labourers in processing, manufacturing, and utilities	0.70%	0.32%	0.51%	0.64%
Industry
Agriculture	1.95%	0.71%	1.70%	1.03%
Forestry and logging and support activities for forestry	0.36%	0.06%	0.27%	0.15%
Fishing, hunting, and trapping	0.20%	0.08%	0.19%	0.06%
Mining, quarrying, and oil and gas extraction	3.30%	0.72%	3.16%	0.59%
Utilities	1.53%	0.53%	1.19%	0.52%
Construction	16.36%	3.09%	13.29%	2.08%
Manufacturing, durable goods	7.15%	1.62%	7.44%	2.46%
Manufacturing, non-durable goods	5.03%	2.60%	5.10%	3.38%
Wholesale trade	3.76%	2.15%	4.94%	2.24%
Retail trade	6.88%	7.70%	7.56%	8.30%
Transportation and warehousing	7.87%	2.27%	7.41%	3.10%
Finance and insurance	5.37%	5.77%	5.63%	6.37%
Real estate and rental and leasing	1.84%	1.54%	1.90%	1.72%
Professional, scientific, and technical services	9.65%	8.74%	8.56%	6.95%
Business, building, and other support services	3.23%	3.08%	3.40%	3.35%
Educational services	4.15%	13.31%	5.11%	15.20%
Health care and social assistance	5.23%	27.48%	5.07%	24.30%
Information, culture, and recreation	3.99%	3.34%	4.06%	2.70%
Accommodation and food services	2.83%	4.20%	3.32%	4.93%
Other services (except public administration)	3.44%	4.01%	3.21%	3.91%
Public administration	5.89%	7.00%	7.49%	6.65%
Full-time	95.26%	78.53%	95.33%	78.15%
Job tenure with employer (months)	73.92 (64.00)	70.67 (59.59)	104.57 (78.90)	93.55 (78.79)
Class of worker
Public sector	15.87%	34.24%	18.21%	33.86%
Private sector	66.99%	53.56%	61.36%	53.51%
Self-employed	17.14%	12.20%	20.42%	12.64%
Age group, y
25–29	8.64%	15.08%	0.73%	1.74%
30–34	27.20%	33.17%	3.88%	8.53%
35–39	34.14%	34.47%	18.71%	26.11%
40–44	21.82%	15.04%	35.19%	35.82%
45–49	6.68%	2.12%	27.88%	22.54%
50–54	1.52%	0.12%	13.61%	5.26%
Marital status
Married/common-law	97.88%	90.93%	93.30%	82.19%
Previously married	0.80%	3.31%	3.72%	10.54%
Never married	1.32%	5.77%	2.99%	7.27%
Immigration status
Immigrant, landed ≤ 10 y earlier	16.39%	14.22%	9.56%	9.27%
Immigrant, landed > 10 y earlier	15.34%	11.97%	21.80%	21.35%
Non-immigrant	68.27%	73.80%	68.64%	69.38%
Province
Newfoundland and Labrador	1.07%	1.26%	1.33%	1.44%
Prince Edward Island	0.42%	0.45%	0.45%	0.51%
Nova Scotia	2.22%	2.32%	2.12%	2.47%
New Brunswick	1.49%	1.61%	2.21%	2.22%
Quebec	23.31%	25.24%	22.11%	22.30%
Ontario	37.07%	36.49%	39.82%	38.21%
Manitoba	3.96%	3.85%	3.54%	3.50%
Saskatchewan	3.37%	3.25%	3.43%	3.24%
Alberta	14.71%	13.69%	12.76%	13.21%
British Columbia	12.38%	11.83%	12.23%	12.89%

Note: standard deviations are in parentheses.

^an.e.c. = not elsewhere classified.