Interaction effects were found between the factors step and block, b = 0.033, p =.001, indicating that participants' categorizations became, overall, less categorical as the experiment progressed; and between the factors block and precursor, b = -0.040, p =.010, reflecting the fact that the effect of precursor became smaller toward the end of the experiment, although it was never absent.
Additionally, to determine whether male and female politicians might be categorized differently, we calculated the percentage of correct categorizations for each target by aggregating across participants' categorizations.
These data therefore suggest that participants' categorizations of targets as Democrats and Republicans may relate to stereotypes of Democrats as warm and Republicans as powerful [24], [25].
In contrast, when hairstyles, eyes, mouths, and outer face shape were removed, participants' categorizations were statistically equivalent to their judgments of the full photos in Study 1.
Participants' categorizations of the targets' political affiliations were significantly greater than chance guessing [M = .62, SD = .12; t(23) = 4.91, p<.001, r = .72] and measures of response bias showed a proclivity among participants to categorize targets as Democrats more often than Republicans (M = −.05, SD = .11).11
The participant categorization was compared to the reference standard using receiver operator characteristic (ROC) curves plotting sensitivity against the specificity at each cut-off for each modality.
Experiment 2B considers the effect of inversion on face categorization by having participants categorize faces as elongated or compressed.
The top ten frequency and importance rated items are provided in Table 2.>> Participant categorizations were compared to the categories established for the experience sampling data collection.
According to this model [9], [15] participants make categorization judgements on the basis of the similarity of the test items to an episodic representation of the study items.
