Dependents as signals of mate value in an online dating context
Bibliographic record
Abstract
Sexual strategies theory indicates that humans can adopt short-and long-term mating strategies, producing sex-and strategy-specific mating behaviours due to asymmetries in obligate parental investment into children.Consequently, demonstrating an ability and willingness to invest in a mate and offspring is highly desired under long-term mating contexts -especially by women.Investment may be financial and/or based on social status, as well as the ability to care for a mate and any resulting offspring.While male carers of dependents (i.e., pets and children) have typically been perceived as high-quality mates by women, no studies have examined how dependents are associated with short-and longterm mating strategies.I selected profiles from the online dating platform Plenty of Fish to test the predictions that men seeking a long-term mate will be more likely to display a dependent on their profile, and those who display a dependent will do so more frequently than men seeking short-term mates and women seeking long-term ones.The results show that men seeking long-term mates were more likely to show a dependent and did so more frequently when compared to men seeking short-term mates; however, men and women seeking a long-term mate displayed dependents in a similar fashion.These patterns were driven mainly by the displays of high-investment dependents (children and canines).These findings indicate that men adopting long-term mating strategies are more likely to advertise their investment capabilities compared to those seeking a short-term mate in a modern dating context, which may be used to signal their mate value.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".