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A TALE OF TWO STRATEGIES: LIFE-HISTORY ASPECTS OF FAMILY STRIFE

2000· article· en· W1982299352 on OpenAlexafffund
Scott Forbes, Douglas W. Mock

Bibliographic record

VenueOrnithological Applications · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Winnipeg
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsBroodIncentiveProduction (economics)BiologyEconomicsEcologyMicroeconomics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0230.001

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.

Opus teacher head0.030
GPT teacher head0.268
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2000
Admission routes2
Has abstractyes

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