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Record W2190883695 · doi:10.1177/147470490700500202

A Common, Conceptual Framework for Behavioral Ecology and Evolutionary Psychology

2007· article· en· W2190883695 on OpenAlexaff
Donald W. White, Lawrence M. Dill, Charles Crawford

Bibliographic record

VenueEvolutionary Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsConstruct (python library)Evolutionary psychologyConceptual frameworkEvolutionary ecologyAdaptive behaviorEcologyPsychologyBehavioral ecologyFocus (optics)OrganismCommon coreCognitive scienceCore (optical fiber)Cognitive psychologySocial psychologyComputer scienceSociologyBiologySocial science

Abstract

fetched live from OpenAlex

Since evolutionary psychology and behavioral ecology have much in common despite their using different objects for their study, one might expect these disciplines to share a common conceptual framework with associated definitions. Unfortunately, such agreement does not entirely exist. To address the problem, we propose a common, conceptual framework, the Adaptive Behavioral System (ABS), which organizes behavior within an evolutionary framework around an organism's life history tasks. An ABS includes strategies that use decision rules and employs tactics administered by a hypothesized construct, the Evolved Processing Unit (EPU). The ABS also includes observed or predicted behavior which can be tested experimentally – the ultimate test of construct validity. Use of the proposed framework should help the two disciplines focus on their common, core business of behavior and, ultimately, be to the benefit of both.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.006
Science and technology studies0.0040.026
Scholarly communication0.0100.014
Open science0.0050.006
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0060.001

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 head0.066
GPT teacher head0.422
Teacher spread0.356 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations10
Published2007
Admission routes1
Has abstractyes

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