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Record W2972108831 · doi:10.3390/ijerph16183236

Re-Thinking Ethics and Politics in Suicide Prevention: Bringing Narrative Ideas into Dialogue with Critical Suicide Studies

2019· article· en· W2972108831 on OpenAlexaff
Jennifer White, Jonathan Morris

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2019
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNarrativeNarrative therapyPoliticsField (mathematics)SociologyPsychologyEpistemologyEngineering ethicsPolitical scienceLawEngineeringLiterature

Abstract

fetched live from OpenAlex

The purpose of this paper is to explore the conviviality between practices of narrative therapy and the emerging field of critical suicide studies. Bringing together ideas from narrative therapy and critical suicide studies allows us to analyze current suicide prevention practices from a new vantage point and offers us the chance to consider how narrative therapy might be applied in new and different contexts, thus extending narrative therapy's potential and possibilities. We expose some of the thin, singular, biomedical descriptions of the problem of suicide that are currently in circulation and attend to the potential effects on distressed persons, communities, and therapists/practitioners who are all operating under the influence of these dominant understandings. We identify some cracks in the dominant storyline to enable alternative descriptions and subjugated knowledges to emerge in order to bring our suicide prevention practices more into alignment with a de-colonizing, social justice orientation.

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 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.185
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.128
GPT teacher head0.484
Teacher spread0.357 · 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 teacher head, 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

Citations33
Published2019
Admission routes1
Has abstractyes

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