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Record W1498546547

Youth suicide as a "wild" problem: implications for prevention practice

2012· article· en· W1498546547 on OpenAlexaff
Jennifer White

Bibliographic record

VenueSuicidology online · 2012
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSuicidologyCopycatStrict constructionismMainstreamExpansiveLicenseCriminologyPsychological interventionSuicide preventionPsychologySociologySocial psychologyPoison controlPublic relationsPolitical scienceLawMedicineCognitive science
DOInot available

Abstract

fetched live from OpenAlex

The intent of this article is to explore the idea that youth suicide -which is conceptualized here as an unstable, historically contingent, and unruly problem - cannot be solved, nor contained, through an exclusive reliance on pre-determined, universal or standardized interventions. Informed by a constructionist perspective, social problems like youth suicide are understood as constituted through language and other relational practices. Based on a close reading of the mainstream school-based suicide prevention literature it is argued that youth suicide has largely been constructed as a tame problem, and this in turn places certain limits on what might be thought, said or done in response. By re-imagining youth suicide as a wild and unstable problem that is deeply embedded in local, historical, and relational contexts, more expansive possibilities for thinking, learning and responding might become available. Implications for school-based suicide prevention are discussed. Keywords: suicide, youth, prevention Copyrights belong to the Author(s). Suicidology Online (SOL) is a peer-reviewed open-access journal publishing under the Creative Commons License 3.0. Language: en

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)0.029
metaresearch head score (Gemma)0.039
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 score0.029
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0120.026
Scholarly communication0.0130.015
Open science0.0040.014
Research integrity0.0110.012
Insufficient payload (model declined to judge)0.0060.001

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 head0.279
GPT teacher head0.559
Teacher spread0.280 · 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

Citations37
Published2012
Admission routes1
Has abstractyes

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