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Record W4238085454 · doi:10.29173/jjs53s

Interacting Narratives:

2011· article· en· W4238085454 on OpenAlexaffvenue
Darrell Dobson

Bibliographic record

VenueJournal of Jungian Scholarly Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativeUnconscious mindPerspective (graphical)PsychologyAnalytical psychologyIdentity (music)Narrative inquiryNarrative networkEpistemologyPsychoanalysisSocial psychologySociologyNarrative criticismAestheticsPhilosophyVisual artsLiteratureArt

Abstract

fetched live from OpenAlex

In narrative approaches to teachers’ professional knowledge, identity (one’s story to live by) is generally understood to be constructed and reconstructed through conscious intention (Chosen Narratives) and through contextual influences (Life Narratives). It is possible and necessary to go further, to describe a third fundamental influence. Using the concept of Self Narratives allows teachers and teacher educators to acknowledge and work with the inevitable and powerful unconscious dynamics that influence their teaching practice and the ongoing construction and reconstruction of their professional knowledge. The concept of Self Narratives integrates the theories and practices of depth psychology, particularly Jungian analytical psychology, into narrative approaches to teachers’ professional knowledge. Recognizing the unconscious mind as profoundly influential is a position overlooked by more familiar schools of educational psychology, and a Jungian perspective considers the unconscious mind as ultimately helpful and holistic, a position that varies from other schools of depth psychology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0080.013
Scholarly communication0.0160.027
Open science0.0020.017
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0190.003

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 head0.343
GPT teacher head0.448
Teacher spread0.105 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2011
Admission routes2
Has abstractyes

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