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Record W2124185868 · doi:10.1177/2158244013503836

Island Lives

2013· article· en· W2124185868 on OpenAlexaffabout
Bettina Heinz, Devon MacFarlane

Bibliographic record

VenueSAGE Open · 2013
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsTransgenderNeeds assessmentHealth careService providerPsychologyNursingGerontologyMedical educationService (business)SociologyMedicinePolitical scienceGender studiesBusinessSocial science

Abstract

fetched live from OpenAlex

In 2010-2011, the Vancouver Island Transgender Needs Assessment, a community-based, applied research project, sought to identify the health and social needs of trans people on Vancouver Island, British Columbia, Canada. An advisory board consisting of trans-identified community members and trans-service providers guided this descriptive analysis. A total of 54 individuals identifying as transgender participated in a survey modeled after the TransPULSE Ontario instrument. Of the participants, 43% identified on the transmasculine spectrum, 39% on the transfeminine spectrum, and 18% as transgender/genderqueer only. Participants were surveyed in regard to education, employment, and income; housing; health care needs and services; suicidality; violence; life satisfaction and attitudes toward self; posttransition experiences; and community belonging. They reported health care, social support, and public education/acceptance as top needs. The article concludes with a specific needs profile and a community-generated set of recommendations stressing the need for an island-based information and resourcing center.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.231
Threshold uncertainty score0.773

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2310.058

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 head0.042
GPT teacher head0.396
Teacher spread0.353 · 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

Citations26
Published2013
Admission routes2
Has abstractyes

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