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Record W1592678725 · doi:10.3390/socsci4030563

The GSA Difference: LGBTQ and Ally Experiences in High Schools with and without Gay-Straight Alliances

2015· article· en· W1592678725 on OpenAlexafffund
Tina Fetner, Athena Elafros

Bibliographic record

VenueSocial Sciences · 2015
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLesbianHarassmentQueerTransgenderPsychologyAllianceSexual orientationHomosexualitySexual identityGender studiesDiversity (politics)HeteronormativityPedagogySociologyHuman sexualitySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

We examine the lived experiences of high-school students who participated in lesbian, gay, bisexual, transgender, and queer (LGBTQ)-centered activism of some kind, highlighting the promise of gay-straight alliance groups by comparing the experiences of students at schools with gay-straight alliances (GSA schools) with the experiences of students at schools that did not have an LGBTQ-specific group (no-GSA schools). We compare students at GSA and no-GSA schools based on their experiences of harassment, experiences of support from authority figures, and patterns of friendships. We find that students at both types of schools experienced harassment and heard negative comments about lesbian and gay people. However, students at GSA schools reported more support from teachers and administrators than students at no-GSA schools, who have stories of teachers and administrators actively opposing equality for LGBTQ people. Students at GSA schools reported a wide variety of friendships across sexual identities, while students at no-GSA schools felt more isolated and withdrawn. This much-needed qualitative comparative analysis of students’ experiences brings a human face to the improved quality of life that schools with gay-straight alliances can bring to young people.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.093
GPT teacher head0.417
Teacher spread0.323 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations39
Published2015
Admission routes2
Has abstractyes

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