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Record W2209059361 · doi:10.1089/lgbt.2015.0046

Sociodemographic Differences by Survey Mode in a Respondent-Driven Sampling Study of Transgender People in Ontario, Canada

2015· article· en· W2209059361 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLGBT Health · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsToronto Metropolitan University
FundersCanadian Institutes of Health Research
KeywordsRespondentTransgenderSampling frameSurvey data collectionSampling (signal processing)Survey researchSurvey methodologyPsychologyTransgender peopleDemographyGeographyMedicineEnvironmental healthPopulationSociologyApplied psychologyPolitical scienceStatisticsComputer science

Abstract

fetched live from OpenAlex

PURPOSE: To describe survey mode uptake and sociodemographic differences by mode among respondents to a respondent-driven sampling survey of transgender people in Ontario, Canada. Survey mode was left to participant choice. METHODS: Data were collected from 433 transgender Ontarians in 2009-2010 through a self-administered questionnaire, available online, by paper copy, or by telephone with language interpretation. RESULTS: Paper respondents (9.5%) were significantly more likely to be Aboriginal or persons of color, underhoused, sex workers, and unemployed or receiving disability benefits. CONCLUSION: In Canada and similar high-income countries, sampling transgender populations that are diverse with respect to social determinants of health may be best carried out with multimode surveys.

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.

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)0.030
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.478
GPT teacher head0.479
Teacher spread0.000 · 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