MétaCan
Menu
Back to cohort
Record W4403514360 · doi:10.26522/ssj.v18i3.4067

“They can’t cope”: Youth Self-injury and Risk Discourse in Canadian News Media

2024· article· en· W4403514360 on OpenAlexaffvenueabout
Sarah Redikopp

Bibliographic record

VenueStudies in Social Justice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsYork University
Fundersnot available
KeywordsPolitical scienceAdvertisingMedia studiesSociologyBusiness

Abstract

fetched live from OpenAlex

Epidemics of self-injury are increasingly framed as public health crises and risk facing youth in Canada. This article examines the discursive construction of youth self-injury as risk in mainstream Canadian news articles through a neoliberal governmentality framework. It argues that self-injury risk discourses are consistent with neoliberal mental health paradigms, which individualize and depoliticize distress while responsibilizing individuals for recovery and wellbeing. The construction of youth self-injury in terms of risk simultaneously undergirds the surveillance, regulation, and coercive control of self-injuring subjects. Based on a critical discourse analysis of Canadian news articles addressing the problem of youth self-injury, this article identifies and discusses three interrelated themes from study findings: social (media) contagion, failed resilience, and system overwhelm. Ultimately, it suggests that the construction of self-injury in terms of risk frames self-injuring youth as failed neoliberal subjects. Risk discourses are therefore incompatible with social justice paradigms in mental health.

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)0.021
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 score0.093
Threshold uncertainty score0.678

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.007
Science and technology studies0.0270.020
Scholarly communication0.0210.007
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.039
GPT teacher head0.387
Teacher spread0.348 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueStudies in Social JusticeSame topicCrime, Deviance, and Social ControlFrench-language works237,207