The merit of meritocracy.
Bibliographic record
Abstract
We argue that the preference for the merit principle is a separate construct from hierarchy-legitimizing ideologies (i.e., system justification beliefs, prejudice, social dominance orientation), including descriptive beliefs that meritocracy currently exists in society. Moreover, we hypothesized that prescriptive beliefs about merit should have a stronger influence on reactions to the status quo when hierarchy-legitimizing ideologies are weak (vs. strong). In 4 studies, participants' preference for the merit principle and hierarchy-legitimizing ideologies were assessed; later, the participants evaluated organizational selection practices that support or challenge the status quo. Participants' prescriptive and descriptive beliefs about merit were separate constructs; only the latter predicted other hierarchy-legitimizing ideologies. In addition, as hypothesized, among participants who weakly endorsed hierarchy-legitimizing ideologies, the stronger their preference for the merit principle, the more they opposed selection practices that were perceived to be merit violating but the more they supported practices that were perceived to be merit restoring. In contrast, those who strongly endorsed hierarchy-legitimizing ideologies were always motivated to support the status quo, regardless of their preference for the merit principle.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".