MétaCan
Menu
Back to cohort
Record W2089539158 · doi:10.1002/mde.1292

Applying evolutionary psychology in understanding the Darwinian roots of consumption phenomena

2006· article· en· W2089539158 on OpenAlexaff
Gad Saad

Bibliographic record

VenueManagerial and Decision Economics · 2006
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsConcordia University
Fundersnot available
KeywordsEvolutionary psychologyConsumption (sociology)DarwinismConsumer behaviourCausationProximate and ultimate causationPreferenceEpistemologyConsumer researchCognitionSociologyPositive economicsPsychologyCognitive scienceSocial scienceSocial psychologyEconomicsMarketingPhilosophyMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Consumer scholars have amassed an impressive body of knowledge using a wide range of methodological approaches and paradigms. Despite the scientific rigor of the consumer behavior discipline, most scholars that have reviewed the field agree that it has yielded a fragmented and confused literature. It is argued here that this is in part due to the near paucity of evolutionary‐based theorizing within the theoretical frameworks used by consumer scholars. While evolutionary psychology focuses on ultimate causation namely the adaptive origins of a particular cognition, emotion, preference, or behavior, the consumer behavior discipline has overwhelmingly addressed proximate mechanisms. Both levels of analyses are needed for a full understanding of consumption phenomena. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.007
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.063
GPT teacher head0.323
Teacher spread0.261 · 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

Citations51
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueManagerial and Decision EconomicsSame topicEvolutionary Psychology and Human BehaviorFrench-language works237,207