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Record W2154189435 · doi:10.1521/jsyt.2013.32.4.33

Assessment System of Narrative Change

2013· article· en· W2154189435 on OpenAlexvenueno aff
Joana Sequeira, Madalena Alarcão

Bibliographic record

VenueJournal of Systemic Therapies · 2013
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeConnotationReflexivityPsychologyNarrative inquirySociologyLiteratureLinguisticsSocial scienceArt

Abstract

fetched live from OpenAlex

The Assessment System of Narrative Change (ASNC) is a method to evaluate narratives in systemic post-modern therapies. ASNC was conceived to describe narrative changes of the system (families, couples, or/and individuals) and integrates seven main dimensions: (A) singularities, (B) nature of the story, (C) narrative connotation, (D) telling of the story, (E) narrative reflexivity, (F) central themes of the session, and (G) alternative behaviors. This system foresees investigation uses (description of system narratives, identification of relevant changing dimensions), clinical uses (narrative diagnoses and evaluation of changing potential, therapy orientation) and training uses (development of skills in educational systemic post-modern orientated programs for therapists).

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)0.024
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.004
Science and technology studies0.0030.002
Scholarly communication0.0050.005
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.005

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 head0.027
GPT teacher head0.308
Teacher spread0.281 · 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 designTheoretical or conceptual
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

Citations8
Published2013
Admission routes1
Has abstractyes

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