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Record W4394721989 · doi:10.1177/00221678241242153

Canonical Narratives as a Tool of Analysis in Psychology

2024· article· en· W4394721989 on OpenAlex
Neil Franchuk

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

VenueJournal of Humanistic Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsYork University
Fundersnot available
KeywordsNarrativePsychologyEpistemologySociologyPsychoanalysisPhilosophy

Abstract

fetched live from OpenAlex

In this article, I develop the concept of canonical narratives, drawing on Jerome Bruner’s (1915-2016) later writings on the central role of culture in shaping human psychology. I argue that we can develop the concept of canonical narratives past its initial purpose in explaining how folk psychology acquires meaning for individuals and develop the concept into a tool of analysis that can shed new light on the broader dialectic between academic psychology and social-cultural environments. I examine the role of canonical narratives in contemporary psychology by focusing on the narrative that human beings are best conceptualized as machines. I argue that not only are psychology’s constructs shaped by social-cultural environments, which have been well established but that their meanings are, to some extent, established through a dialectic with canonical narratives.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.035
GPT teacher head0.403
Teacher spread0.368 · 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