Short-Term and Long-Term Mating Strategies Show Distinct Patterns of Attraction to Dominance and Prestige
Bibliographic record
Abstract
People generally covet high-rank romantic partners. Yet, the multidimensional strategies of attaining social rank (dominance and prestige) and sociosexuality (long-term and short-term mating orientations) leave open the question of which strategies for attaining social rank are coveted, and by whom. We provide greater resolution into understanding attraction to social rank strategies by demonstrating that people with higher long-term mating orientations show an attraction to prestige strategists, but an aversion to dominance strategists, whereas people with higher short-term mating orientations show increased attraction to people who pursue high rank in the form of both dominance and prestige. These effects emerged for men and women across studies measuring partner preferences through personality traits (Study 1) and facial photographs (Study 2). Mate attraction to social rank strategies thus differs by people's mating orientation and the type of social rank strategy, supporting our preregistered hypotheses.
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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 | 0.000 | 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) | 0.004 | 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".