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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 OpenAlexafffundabout
Ayden I. Scheim, Greta R. Bauer, Todd Coleman

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.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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

Citations10
Published2015
Admission routes3
Has abstractyes

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