Bibliographic record
Abstract
This thesis is designed to examine the effects of discrimination on its target. It aims to investigate the psychological, physical, perceptual and behavioral responses that individuals exhibit when faced with racist, sexist and heterosexist as well as other types of discriminatory acts. Through meta-analytic procedures, findings from existing studies investigating the impact of discrimination on the target were gathered and their average effect sizes calculated. A total of 50 empirical studies were identified, from which 84 effect sizes were derived. Using homogeneity analysis techniques, the studies' effect sizes were compared and analyzed. The results show significant heterogeneity in the overall mean effect size (0.38) of discrimination. Subsequent moderator variable investigations indicated that among discrimination acts, sexism had the highest mean effect size (0.64), while among the responses to discrimination, the perceptual factor showed the highest mean effect size (0.65). Additional moderator variables' investigations resulted in significant differences between Canadian and American settings in terms of discrimination acts and responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.114 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.034 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".