Confirmatory Factor and Invariance Analyses of the Motivation to Control Prejudiced Reactions Scale
Why this work is in the frame
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Bibliographic record
Abstract
The present research further examines the psychometric properties of the Motivation to Control Prejudiced Reactions Scale (MCPRS). Particular attention is paid to the replicability of its factor structure and its factorial equivalence across samples of university students from Western Canada (n = 235), Eastern Canada (n = 556) and the mid-Western United States of America (n = 404). Confirmatory factor analysis and invariance analysis were carried out using the Analysis of Moment Structures (AMOS) 7.0. Results showed that while the two-factor structure of the MCPRS was replicated across samples, the original model required refinement to produce acceptable model fit (i.e., each sample had a slightly different model). Partial measurement invariance also was demonstrated for a subset of items on the MCPRS. The implications of the results, in terms of future use of the MCPRS are discussed, and limitations of the current study are outlined.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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