  As is the case with terms like “attitude” and “propositional,” psychologists and philosophers tend to use the term “trait” in different ways. In psychology, trait-like constructs are stable over time and across situations. If you have always disliked eating pork, and never eat it no matter the context, then your feelings toward pork are trait-like. If you sometimes decline to eat pork but sometimes indulge, depending on the company or your mood, then your feelings are more “state”-like. In the psychologist’s sense, significant evidence suggests that implicit bias is more state-like than trait-like. Multiple longitudinal studies have found that individuals’ scores on implicit measures vary significantly over days, weeks, and months, much more so than individuals’ scores on corresponding explicit measures (Cooley &amp; Payne 2017; Cunningham et al. 2001; Devine et al. 2012; Gawronski et al. 2017). Of course, the significance of this depends on one’s theory of implicit bias. If implicit measures are theorized to capture spontaneous affective reactions (as APE suggests; §2.2), then contextual and temporal variability in performance should be predicted (because, for example, one’s immediate reactions to images of women leaders will likely be different after watching a documentary about Ruth Bader Ginsburg than after watching Clueless). However, if implicit measures are meant to “diagnose” stable features of individuals like political party affiliation, then far less variation should be expected. Another possibility is that measurement error contributes significantly to the instability of scores on implicit measures. The fact that methodological improvements have in some cases improved the temporal stability of participants’ performance supports this idea (e.g., Cooley and Payne 2017).