Selective advantage of redirected helping in a viscous population
Bibliographic record
Abstract
When a brood fails, the failed parent can help a neighbor rear its offspring. This behavior is known as redirected helping and occurs in various species. The advantage of redirected helping may seem obvious, provided the individual whose brood fails helps a related neighbor: The helper at least gains indirect fitness by redirecting its parental effort. However, complications arise when considering a viscous population, where individuals remain on or close to their natal site. In such a population, individuals compete with relatives, which dilutes the advantage of helping and may counteract it altogether. This raises a question: when can we expect redirected helping to evolve in a viscous population? We address this question with inclusive fitness models. We find that redirected helping can always be favored in a viscous population, provided the cost is sufficiently low. We also identify life-history features-like survival, dispersal, and brood-failure rate-that promote redirected helping. The effect of these life-history features, in general, depends on which component of fitness (survival or fecundity) benefits from help and how brood failure varies among demes. Unlike previous authors, we find that helping can be more strongly promoted when it provides survival rather than fecundity benefits.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".