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Record W2956781872 · doi:10.1111/ajsp.12381

An introduction to the theory of sociocultural models

2019· article· en· W2956781872 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.

Bibliographic record

VenueAsian Journal Of Social Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSociocultural evolutionConstruct (python library)Set (abstract data type)Agency (philosophy)Scripting languageSociologyOntologyStructure and agencyActivity theoryPsychologyPersonal construct theoryConceptual modelSocial psychologyEthnographyEpistemologyComputer scienceSocial sciencePedagogy

Abstract

fetched live from OpenAlex

This article introduces the theory of sociocultural models ( TSCM ) along with its propositions, historical and conceptual foundations, ontology, and the methodology for its applications in sociocultural research. Sociocultural models ( SCM s) are a structured set of prescriptions for people to interpret the world, communities, other people, and themselves; they are a set of scripts for acting in accord with these interpretations. These models are developed by people's cultural communities, and they are learned and internalized by their members as validated recipes for their lives and actions. Members of communities continuously co‐construct their SCM s by enacting them through their everyday interactions. Culture is described as a distributed network of specialized SCM s that guides community members’ lives in different domains. According to the TSCM , to fully understand the nature of people’ actions and experiences, researchers first must examine the system of SCM s that these people were born into—the public aspects of SCM s. Subsequently, researchers must investigate how these people act, experience, and live through these models—the internalized aspects of SCM s—and determine what roles their autonomous agency and self‐determination play in their existence. To study SCM s, researchers use methods such as person‐centered ethnography, interviews, and experiments.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.395
Teacher spread0.363 · 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