MétaCan
Menu
Back to cohort

A Cultural Neuroscience Approach to the Biosocial Nature of the Human Brain

2012· review· en· W2135777221 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Psychology · 2012
Typereview
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
FundersNational Key Research and Development Program of ChinaCanadian Institutes of Health ResearchVolkswagen FoundationNational Natural Science Foundation of ChinaHope for Depression Research Foundation
KeywordsBiosocial theoryCultural neuroscienceSociocultural evolutionPsychologyBrain functionCognitive scienceFunction (biology)Human brainSocial neuroscienceNeuroscienceEpistemologySociologyCognitionSocial psychologySocial cognitionAnthropologyPersonality

Abstract

fetched live from OpenAlex

Cultural neuroscience (CN) is an interdisciplinary field that investigates the relationship between culture (e.g., value and belief systems and practices shared by groups) and human brain functions. In this review we describe the origin, aims, and methods of CN as well as its conceptual framework and major findings. We also clarify several misunderstandings of CN research. Finally, we discuss the implications of CN findings for understanding human brain function in sociocultural contexts and novel questions that future CN research should address. By doing so, we hope to provide a clear picture of the CN approach to the human brain and culture and to elucidate the intrinsically biosocial nature of the functional organization of the human brain.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.658
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.210
GPT teacher head0.520
Teacher spread0.310 · 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