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Record W4292761100 · doi:10.1177/07435584221115351

Age, Autonomy, and Authority of Knowledge: Discursive Constructions of Youth Decision-Making Capacity and Parental Support in Transgender Minors’ Accounts of Healthcare Access

2022· article· en· W4292761100 on OpenAlexaff
Alic Shook, Diana M. Tordoff, April Clark, Robin Hardwick, Will St. Pierre Nelson, Ira Kantrowitz‐Gordon

Bibliographic record

VenueJournal of Adolescent Research · 2022
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsSimon Fraser University
FundersUniversity of WashingtonRobert Wood Johnson Foundation
KeywordsAutonomyTransgenderConfidentialityAmbiguityHealth careFocus groupPsychologySociologySocial psychologyGender studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

While access to care is known to improve health outcomes for transgender youth, these youth often face challenges in accessing care related to decision-making capacity and the legal limitations regarding age of consent. In this study, we utilize discourse analytic methods to identify how notions of age, autonomy, and authority of knowledge influence transgender youths’ ability to make agentic decisions about their bodies and health, and better understand the power dynamics present in youths’ relations with parents and providers. We conducted 11 one-on-one interviews with transgender youth between the ages of 13 to 17 and one focus group with high school-age trans youth ( n = 8) in the Seattle-Tacoma area of Washington state. We identified two sets of discourses: (1) discourses of autonomy, which included self-determination, confidentiality, and authority of knowledge and (2) discourses of support, which included role ambiguity, trust/mistrust, and good and bad parents. Findings from this study highlight power dynamics present in trans youths’ relations with parents and providers.

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)0.012
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.022
Scholarly communication0.0070.007
Open science0.0010.007
Research integrity0.0010.003
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 head0.200
GPT teacher head0.500
Teacher spread0.300 · 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 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

Citations10
Published2022
Admission routes1
Has abstractyes

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