Terminal Investment Strategies and Male Mate choice: Extreme Tests of Bateman
Bibliographic record
Abstract
Bateman's principle predicts the intensity of sexual selection depends on rates of increase of fecundity with mating success for each sex (Bateman slopes). The sex with the steeper increase (usually males) is under more intense sexual selection and is expected to compete for access to the sex under less intense sexual selection (usually females). Under Bateman and modern refinements of his ideas, differences in parental investment are key to defining Bateman slopes and thus sex roles. Other theories predict sex differences in mating investment, or any expenditures that reduce male potential reproductive rate, can also control sex roles. We focus on sexual behaviour in systems where males have low paternal investment but frequently mate only once in their lifetimes, after which they are often killed by the female. Mating effort (=terminal investment) is high for these males, and many forms of investment theory might predict sex role reversal. We find no qualitative evidence for sex role reversal in a sample of spiders that show this extreme male investment pattern. We also present new data for terminally-investing redback spiders (Latrodectus hasselti). Bateman slopes are relatively steep for male redbacks, and, as predicted by Bateman, there is little evidence for role reversal. Instead, males are competitive and show limited choosiness despite wide variation in female reproductive value. This study supports the proposal that high male mating investment coupled with low parental investment may predispose males to choosiness but will not lead to role reversal. We support the utility of using Bateman slopes to predict sex roles, even in systems with extreme male mating investment.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".