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Record W2170058287 · doi:10.7202/1017478ar

Suicidality among trans people in Ontario: Implications for social work and social justice

2013· article· en· W2170058287 on OpenAlexaffvenueabout
Greta R. Bauer, Jake Pyne, Matt Caron Francino, Rebecca Hammond

Bibliographic record

VenueService social · 2013
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsRainbow Health OntarioWestern University
Fundersnot available
KeywordsTransphobiaTransgenderSuicide preventionSocial workPoison controlPsychologySociologyCriminologyPolitical scienceMedicineGender studiesEnvironmental health

Abstract

fetched live from OpenAlex

While transgender and transsexual (trans) communities have been documented to experience high rates of suicidality, little attention has been paid to how this may vary based on experiences of social injustice. Using survey data from the Trans PULSE Project (n=433), we estimated that suicidal thoughts were experienced by 36% of trans Ontarians over the past year, and that 10% attempted suicide during that time. Moreover, we documented that youth and those experiencing transphobia and lack of support are at heightened risk. Suicidality varied greatly by medical transition status, with those who were planning to transition sex, but who had not yet begun, being most vulnerable. Recommendations are made for improving wellbeing in trans communities, through policy advocacy, service provision, access to transition care, and fostering accepting families and communities.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.055
GPT teacher head0.371
Teacher spread0.315 · 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 designObservational
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

Citations87
Published2013
Admission routes3
Has abstractyes

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