Female mate preference varies with age and environmental conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sexual selection and mate choice are dynamic processes that can be influenced by a variety of environmental and social factors, which have been well studied in a range of taxa. However, in humans, the environmental factors that influence regional variation in preference for mate attributes remain poorly understood. In addition, underlying variation based on individual age may strongly influence mate preferences. In this study, we examined written descriptions of preferred mates from the online dating profiles of 1111 women from 26 cities across Canada. We grouped the words describing preferred mates into four categories: resource holding potential, physical attractiveness, activities and interests, and emotional appeal. We then asked whether variation in environmental (sex ratio, population size and population density), economic (population income) and individual factors (age) predicted variation in the relative importance of these four categories of female mate preference. Sex ratio was the best predictor of preference for the physical attractiveness and the activities and interests of potential mates, with women in male-biased cities placing more emphasis on physical attractiveness and less emphasis on activities and interests. Age was the best predictor of preference for resource holding potential, with younger individuals placing more emphasis on this trait. No factors were strong predictors of variation in preference for emotional appeal, perhaps because this trait was highly valued in all populations. This work supports a growing body of literature demonstrating that mate choice and mate preferences are often dynamic and can be influenced by individual and environmental variation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.002 | 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 it