Looking for Ms. Right: Allocating Attention to Facilitate Mate Choice Decisions
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
Through various signals, the human body provides information that may be used by receivers to make decisions about mate value. Here, we investigate whether there exists a complementary psychological system designed to selectively attend to these signals in order to choose, and direct effort toward the acquisition of, a potential mate. We presented young men with three images of the same woman (six women in total) simultaneously, varying the waist-to-hip ratio (WHR) of each image while holding other traits constant. While participants chose their preferred image, we monitored visual attention using an infrared eye-tracker. We found that participants focused their attention selectively on body regions known to provide reproductive information in a manner consistent with the research hypothesis: Reproductively relevant body regions, especially the head and breasts, received the most visual attention. Likewise, images with lower WHRs and reproductively relevant regions in images with lower WHRs received the most visual attention and were chosen as most attractive. Finally, irrespective of WHR size, participants fixated more often and for longer durations on the images that they selected as most attractive.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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