The integrative prejudice framework and different forms of weight prejudice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We use the integrative prejudice framework to further our understanding of weight prejudice, while simultaneously testing the generalizability of this framework. Participants completed measures of implicit and explicit weight prejudice, egalitarian-based nonprejudicial goals, and perceived weight discrimination. In line with predictions of the integrative prejudice framework based on cognitive consistency principles, implicit and explicit weight prejudice were positively related when nonprejudicial goals were low and perceived discrimination was high, and when nonprejudicial goals were high and perceived discrimination was low, reflecting central components of old-fashioned and modern prejudice, respectively. Furthermore, implicit and explicit weight prejudice were negatively related when nonprejudicial goals and perceived discrimination were both high, reflecting central components of aversive prejudice. In addition to supporting the generalizability of the integrative prejudice framework, this research demonstrates that weight prejudice may operate in different forms that map onto existing theories of prejudice.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it