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Record W2280709093 · doi:10.4236/psych.2015.614185

Systematic Review of Studies Measuring the Impact of Educational Programs against Homophobia, Transphobia and Queerophobia in Secondary Schools of North America, Western Europe and Australia

2015· article· en· W2280709093 on OpenAlexaff
Germano Vera Cruz

Bibliographic record

VenuePsychology · 2015
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyPrejudice (legal term)TransphobiaInclusion (mineral)HeterosexismVerbal abuseAllianceDevelopmental psychologyClinical psychologySocial psychologyTransgenderHomosexualitySuicide preventionPoison control

Abstract

fetched live from OpenAlex

The objective of this study is to review the studies measuring the impact of extra-curricular and intra-curricular educational programs designed to reduce the prejudice, verbal, psychological and physical violence against LGBTQ students in secondary schools, and assess the degree of effectiveness of those programs to improve the situation of students from sexual minorities, as well as to change the attitude and behavior of heterosexual and cisgender students towards their LGBTQ peers. Given the inclusion and exclusion criteria, 13 studies were identified as relevant. The majority of these studies were on Gay-Straight Alliance (GSA), and the other focused on extracurricular seminars type programs (ECS) conducted by volunteers of LGBTQ associations and intra-curricular programs (ICP) administered by teachers. On one hand, the results show a significant, systematic and sustainable positive impact of GSA on both the school life of LGBTQ students and on the attitudes and behaviors of heterosexual and cisgender students toward their colleagues from sexual minorities; on the other hand, the results show a less effectiveness of ECS/ICP to reduce prejudice, verbal abuse, psychological and physical violence against LGBT students.

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 score0.135
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.108
GPT teacher head0.437
Teacher spread0.329 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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