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Who Are We Missing? The Impact of Requiring Parental or Guardian Consent on Research With Lesbian, Gay, Bisexual, Trans, Two-Spirit, Queer/Questioning Youth

2020· article· en· W3093347040 on OpenAlexafffund
Eli Cwinn, Courtney Cadieux, Claire V. Crooks

Bibliographic record

VenueJournal of Adolescent Health · 2020
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsLondon Health Sciences CentreWestern University
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsLesbianGuardianPsychologyQueerParental consentSexual orientationSexual identitySexual minorityAnxietyMental healthClinical psychologySocial psychologyInformed consentDevelopmental psychologyPsychiatryGender studiesMedicineHuman sexualitySociologyPolitical science

Abstract

fetched live from OpenAlex

PURPOSE: The purpose was to examine whether a requirement for parental or guardian consent systematically limits which lesbian, gay, bisexual, trans, two-spirit, queer/questioning (LGBT2Q+) youth participate in research. METHODS: A total of 60 LGBT2Q+ youth (aged 14-18 years) completed measures assessing gender and sexual minority identity, depression and anxiety, help-seeking intentions, and social support. RESULTS: A substantial proportion (37.6%) of youth reported that they would not have participated in the research if parental or guardian consent was required. Those who would not have participated had more negative attitudes about their sexual and gender identity, less family support, lower levels of help-seeking intentions, and higher levels of negative affect. CONCLUSIONS: The results suggest that requiring parental or guardian consent may exclude the most at-risk youth. Policy and practice decisions regarding the health and mental health outcomes of LGBT2Q+ youth might be based on incomplete and unrepresentative data.

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)0.577
metaresearch head score (Gemma)0.741
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.423
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5770.741
Meta-epidemiology (narrow)0.0010.003
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0030.002
Science and technology studies0.0180.017
Scholarly communication0.0120.018
Open science0.0070.013
Research integrity0.0170.023
Insufficient payload (model declined to judge)0.0130.002

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 head0.460
GPT teacher head0.538
Teacher spread0.078 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations32
Published2020
Admission routes2
Has abstractno

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