Data from: Testing predictions of inclusive fitness theory in inbreeding relatives with biparental care
Bibliographic record
Abstract
AbstractInclusive fitness theory predicts that parental care will vary with relatedness between potentially caring parents and offspring, potentially shaping mating system evolution. Systems with extra-pair paternity (EPP), and hence variable parent-brood relatedness, provide valuable opportunities to test this prediction. However, existing theoretical and empirical studies assume that a focal male is either an offspring’s father with no inbreeding, or is completely unrelated. We highlight that this simple dichotomy does not hold given reproductive interactions among relatives, complicating the effect of EPP on parent-brood relatedness yet providing new opportunities to test inclusive fitness theory. Accordingly, we tested hierarchical hypotheses relating parental feeding rate to parent-brood relatedness, parent kinship and inbreeding, using song sparrows (Melospiza melodia) experiencing natural variation in relatedness. As predicted, male and female feeding rates increased with relatedness to a dependent brood, even controlling for brood size. Male feeding rate tended to decrease as paternity loss increased, and increased with increasing kinship and hence inbreeding between socially-paired mates. We thereby demonstrate that variation in a key component of parental care concurs with subtle predictions from inclusive fitness theory. We additionally highlight that such effects can depend on the underlying social mating system, potentially generating status-specific costs of extra-pair reproduction.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.018 |
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".