Table 1.

Past Predictions Regarding the Semantic Space of Emotion Recognition

Theory	Dimensionality How many emotions are signaled in facial-bodily behavior?	Conceptualization What concepts capture the recognition of emotion in expression?	Distribution Are emotions perceived as discrete clusters or continuous gradients?
Basic emotion theory	Perceptual judgments rely on a variety of distinct emotions, ranging from six in early theorizing to upwards of 20 in more recent theorizing.	Emotion categories capture the underlying organization of emotion recognition. Ekman (1992): “Each emotion has unique features … [that] distinguish emotions from other affective phenomena.”	Boundaries between categories are discrete. Ekman (1992): “Each of the basic emotions is … a family of related states. … I do not propose that the boundaries between [them] are fuzzy.”
Constructivist theory	Perceptual judgments of expressions will be reducible to a small set of dimensions.	Valence, arousal (and perhaps a few other appraisals) will organize the recognition of emotion.	Categories, constructed from broader properties that vary smoothly and independently, will be bridged by continuous gradients.
	Barrett (2017): “Emotional phenomena can be understood as low dimensional features.”	Russell (2003): “Facial, vocal … changes … are accounted for by core affect [valence and arousal] and … instrumental action.”	Barrett (2006): “evidence … is inconsistent with the view that there are kinds of emotion with boundaries that are carved in nature.”
Methods	Multidimensional reliability assessment.	Statistical modeling applied to large, diverse data sets.	Visualization techniques, direct analysis of clusters, and continuous gradients.