Foundational work in the medical image perception literature by Kundel et al. (1978) categorized target miss errors as caused by "search, recognition or decision" errors.
To facilitate comparison we categorized target ages into 6 age groups: 0-5 years (pre-school children), 6-11 years (junior school children), 12-15 years (high school children), 16-39 young (young adults), 40-64 years (middle-aged adults) and 65 years or over (elderly).
Watkins (1991) found effects of normalization when listeners categorized targets on an //-to-/ɛ/ continuum that were presented after intelligible precursor sentences that had been filtered.
In Experiment 1a, participants categorized targets on a [pIt]-to-[pɛt] continuum (an F1 distinction), presented after speech precursors with an increased or a decreased average F1 level.
First, in both the SRC and IAT, participants are instructed explicitly to categorize target stimuli (e.g. substance-related or neutral) with 'approach' in one block and 'avoid' in another block of the task (in the SRC, but not the IAT, this is accompanied by a symbolic approach or avoidance movement of a manikin).
Research on household energy conservation often categorizes targeted behaviours by their behavioural attributes (e.g., savings, cost, frequency).
A similar analysis performed by categorizing targets according to their p values (Fig. 4g/h) showed that the pairwise overlap between high confidence (low p value) targets of different fingerprints were significantly higher (on average 47% overlap) as compared to low confidence targets (high p value, on average 24% overlap).
Participants were able to categorize targets according to their political affiliation significantly better than chance guessing [M = .57, SD = .08; t(28) = 4.41, p<.001, r = .64] and measures of response bias indicated that participants showed a slight tendency to categorize targets as Republicans more often than Democrats (M = .01, SD = .04).04
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 use of FIC as an indicator of the effectiveness of immunization programs leads to categorizing targeted children into two groups: those fully vaccinated and those not fully vaccinated.
We therefore calculated for each target the percentage of perceivers who had categorized the target as a Democrat in Study 2 and correlated these values with both Power and Warmth.
