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Record W4379522482 · doi:10.32920/23302214

An Exploration of Suicide Reporting in Canadian Newspapers

2023· preprint· en· W4379522482 on OpenAlexaffabout
Siena Maxwell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsToronto Metropolitan UniversityCentre for Social InnovationYork UniversityWestern University
Fundersnot available
KeywordsNewspaperReflexivityContext (archaeology)PoliticsPublicationCriminologyMental illnessSociologyMedia studiesPolitical sciencePsychologyHistoryPsychiatryLawMental healthSocial science

Abstract

fetched live from OpenAlex

<p>This paper explores how two large Canadian newspaper outlets cover and publish cases of suicide over the past 41 years. Utilizing a mad studies lens, this research employs critical discourse analysis to illuminate how a medicalized and individualized model of mental illness has dominated the way we view madness. As a result, the coverage of mad individuals who choose suicide consistently pathologizes and blames them, while reinforcing the notions that mad people are violent, criminal and in need of medical control. Also missing from the dialogue is a discussion and recognition of the role of the social, political, cultural, and economic context in which people become mentally distressed. More recently, self-reflexivity on the part of the journalist has grown, impacting the way cases of suicide are covered and discussed.</p>

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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.441
GPT teacher head0.447
Teacher spread0.006 · 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.

Study designBench or experimental
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
Published2023
Admission routes2
Has abstractyes

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