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Record W4250976802 · doi:10.17759/chp.2019150401

Ecocultural Psychology

2019· article· en· W4250976802 on OpenAlex
John W. Berry

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCultural-Historical Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsQueen's University
Fundersnot available
KeywordsEnculturationAcculturationEpistemologySocial psychologyPsychologyPerspective (graphical)Diversity (politics)SociologyCultural psychologyInterpretation (philosophy)EthnographyCultural group selectionCultural diversityCognitive psychologyAnthropologyLinguisticsComputer scienceEthnic group

Abstract

fetched live from OpenAlex

This paper reviews the early and recent theoretical and empirical work in ecocultural psychology. It addresses the question of the origins of similarities and differences in human behavior across cultures and of the relationships between culture and behavior, using the ecocultural framework as a guide. I argue that we are able to provide an interpretation of these relationships if we adopt an ecocultural perspective, in which we assume that basic psychological processes are “universal” in the human species, and that behaviors are “adaptive” to contexts, both ecological and sociopolitical. Within such a framework, we conceptualize cultural and individual behavior as separate phenomena: culture exists apart from particular individuals, but becomes incorporated into all individuals through two main transmission processes (enculturation and acculturation). Hence culture is both an independent and an organismic variable in such a framework. Given this conception, it is possible to carry out empirical work at the two levels. Analyses can then be conducted within levels (the classical ethnographic and individual difference studies) and comparisons be made between levels. The major advantage exists when cultural-level data are used to predict individual and group similarities and differences in behavior. No longer do we need to rely on post hoc interpretations of behavioral similarities and differences across cultures. The ecocultural strategy is both “cultural” and “comparative,” allowing for the “cross-cultural” understanding of human diversity.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.028

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 head0.165
GPT teacher head0.450
Teacher spread0.284 · 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