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Record W4396545788 · doi:10.1521/jsyt.2023.42.4.1

Story-Based and Bottom-Up Accountability With Children Who Have Experienced Trauma: Practices That Focus on Response

2023· article· en· W4396545788 on OpenAlexvenueno aff
Daniel Moss

Bibliographic record

VenueJournal of Systemic Therapies · 2023
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityFocus (optics)PsychologyDevelopmental psychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Narrative and systemic therapists emphasize the context of children's stories while helping them to connect their actions, emotions and meaning making. Rather than only diagnosing and correcting the effects of trauma on the child's body and brain, narrative and systemic therapists help children to describe their responses to experiences of trauma. Therapists are challenged to operate within institutions that impose corrective accountability imperatives on children. Therapy can become accountable to educational, social, or legal institutions that require the child's conformity and co-operation. This article examines therapy that recruits children as co-researchers in the meaning-making of their life's experiences, including both the effects and their responses to experiences of trauma. In this way, therapists are accountable to a fascination with what is not yet known, rather than to the reproduction of dominant discourses of correction.

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)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.013
Scholarly communication0.0050.005
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.043
GPT teacher head0.333
Teacher spread0.290 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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