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Record W2552458135 · doi:10.1177/0022022116680481

Nature, Nurture, and Their Interplay

2016· article· en· W2552458135 on OpenAlexaff
Joni Y. Sasaki, Heejung S. Kim

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsYork University
Fundersnot available
KeywordsNature versus nurtureCultural neuroscienceField (mathematics)Cognitive sciencePsychologyEpistemologySociologyNeuroscienceCognitionAnthropology

Abstract

fetched live from OpenAlex

Cultural neuroscience research examines how psychological processes are affected by the interplay between culture and biological factors, including genetic influences, patterns of neural activation, and physiological processes. In this review, we present foundational and current empirical research in this area, and we also discuss theories that aim to explain how various aspects of the social environment are interpreted as meaningful in different cultures and interact with a cascade of biological processes to ultimately influence thoughts and behaviors. This review highlights theoretical and methodological issues, potential solutions, and future implications for a field that aspires to integrate the complexities of human biology with the richness of culture.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.481
Teacher spread0.415 · 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 teacher head, not a consensus.

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

Citations49
Published2016
Admission routes1
Has abstractyes

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