A TALE OF TWO STRATEGIES: LIFE-HISTORY ASPECTS OF FAMILY STRIFE
Bibliographic record
Abstract
Breeding birds can generally be thought of as having evolved life-history traits that tend to maximize lifetime reproductive success. Within this broad pattern, many variations are possible because all traits are co-evolved with numerous others in complex ways. Clutch-size, for example, has long been understood to be frequently lower than the number of young parents are capable of supporting by working at their top capacity, especially in long-lived species. Nevertheless, studies of species with fatal competition among nestmates have shown that parents routinely create one offspring more than they normally will raise, as if counting on brood-reduction to trim family size after hatching. Three general and mutually compatible parental incentives for initial over-production have been identified, with David Lack's resource-tracking hypothesis having received the most attention. Extra sibs can also assist each other in some circumstances, but a third explanation for over-production that has been around for nearly four decades, the insurance hypothesis, has been surprisingly overlooked and, in some cases, actively challenged. It simply posits that parents create extra offspring as back-ups for members of the core brood that chance to die very early. We propose that the skepticism over the role of insurance is misdirected, that having a back-up is virtually automatic as a contributing incentive to parents and, in some taxa, that it provides a necessary and totally sufficient explanation for over-production. Some empirical approaches to the study of the insurance hypothesis are reviewed, in hopes of encouraging further field study of over-production in general, because that process underlies much of the internal conflict observed in avian families.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".