Some bold evolutionary predictions for the future of mating in humans
Bibliographic record
Abstract
Why are many human populations presently ‘imploding’ with below‐replacement fertility? Why are more and more young adults in these societies choosing to remain single and/or childless? Based on first principles of evolutionary theory, predictions can be derived for changes over time in the relative frequency distributions of four traits in humans proposed as the most direct determinants of the propensity to mate and reproduce: attractions to sex, legacy, leisure and parenting. In the past, high fitness was most profoundly determined by strong sex drive and strong legacy drive, especially in males. Female fertility was largely controlled by dominant males, who were then free to engage in attractions to both leisure and legacy through ‘memes’ (as well as through genes, or offspring) without any penalty on fitness. Natural selection in the past, therefore, neither strongly favoured nor strongly disfavoured any particular intrinsic female inclinations or preferences that might affect offspring production. The recent, widespread, and continuing rise in the empowerment of women, however, defines a dramatically different contemporary selection regime, where women are now free to indulge in their evolved attractions to leisure and legacy through memes inherited from predecessors, both of which represent compelling distractions from parenthood. The implications for the future survival of marriage and parenthood as cultural institutions look dismal in the short term, but promising in the long term.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".