RESOURCEFULNESS AND SOCIAL DESIRABILITY TRAIT ASCRIPTIONS OF MALES: AN EVALUATION OF AGE AND SEX
Bibliographic record
Abstract
The purpose of this study was to evaluate the effects of age and sex on trait ascriptions toward male targets. Young ( n = 40) and elderly ( n = 40) participants rated young and elderly male targets on a number of traits of social desirability and resourcefulness using the Social Desirability Index (Perlini, Bertolissi, & Lind, 1999). Consistent with previous research on female targets, male targets were considered more socially desirable when they were young; moreover, the social desirability of the target male was considered more favorable when undertaken by an elderly evaluator. Elderly participants rated the young male target as more resourceful than the elderly male target, and more resourceful than the young participants rated the young male target. Results are discussed in terms of evolutionary and role theories of social behavior.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".