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Record W2007528613 · doi:10.1080/1550428x.2014.941127

Transphobia and Other Stressors Impacting Trans Parents

2015· article· en· W2007528613 on OpenAlexafffundabout
Jake Pyne, Greta R. Bauer, Kaitlin Bradley

Bibliographic record

VenueJournal of GLBT Family Studies · 2015
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsWestern UniversityMcMaster University
FundersInstitute of Gender and HealthCanadian Institutes of Health Research
KeywordsTransphobiaTransgenderRespondentPsychologyStressorGender dysphoriaPsychosocialMental healthClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Limited research regarding transsexual or transgender (trans) parents has often focused on their children. This analysis represents the first published profile of trans parents (N = 110) from a large probability-based sample of trans people (N = 433). The Trans PULSE Project used respondent-driven sampling to collect survey data from trans people in Ontario, Canada. Trans parents differed from nonparents in that they were older, more educated, and had higher personal incomes. Trans parents did not differ significantly from nonparents in the level of transphobia they experienced and many reported being impacted by multiple stressors. A majority felt that being trans had hurt or embarrassed their family, worried about growing old alone because they are trans, or had been made fun of for being trans. A substantial minority had been turned down for a job, had to move away, been hit or beat up, been harassed by police, or been fired from a job because they were trans. Some reported no legal access to their child (18.1%) or having lost custody or having custody reduced because they were trans (17.7%). Recommendations are made for mental health professionals to support trans parents and their families through psychosocial support, family therapy, professional training, and advocacy.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.236
GPT teacher head0.462
Teacher spread0.225 · 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

Citations74
Published2015
Admission routes3
Has abstractyes

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