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School Safety and Connectedness Matter for More than Educational Outcomes

2016· book-chapter· en· W4230532338 on OpenAlexaboutno aff
Elizabeth Saewyc, Yuko Homma

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook-chapter
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSocial connectednessOddsPopulationHealth equityPsychologyAdolescent healthDevelopmental psychologyPublic healthMedicineSocial psychologyEnvironmental healthNursing

Abstract

fetched live from OpenAlex

LGBTQ youth face significant health disparities compared to heterosexual peers. School-based victimization of LGBTQ youth, as well as lower levels of school connectedness and perceived safety at school, have been implicated in those health disparities. Drawing on multivariate and population-based studies throughout the United States and Canada, this chapter explores the evidence that school connectedness can lower the odds of health-compromising behaviors and disparities among different subpopulations of LGBTQ youth. The authors review strategies for fostering school connectedness among the general population and consider how these strategies might fit or might need to be adapted for LGBTQ populations. The authors highlight evidence for programs and policies that improve school connectedness among LGBTQ students that is already available, especially evidence that these programs actually work to reduce health inequities. Schools, as key environments for young people, are important contributors to health for LGBTQ youth.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.003

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 head0.028
GPT teacher head0.295
Teacher spread0.267 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooks→Same topicLGBTQ Health, Identity, and Policy→French-language works237,207→