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Record W2016607574 · doi:10.1080/1047621042000180031

Kids say the funniest things … anti‐homophobia group work in the classroom

2004· article· en· W2016607574 on OpenAlexaboutno aff
Steven Davidoff Solomon

Bibliographic record

VenueTeaching Education · 2004
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLesbianTransgenderObligationHomosexualityHuman sexualityPedagogyPsychologySexual identityEquity (law)SociologyWork (physics)Group workGender studiesPolitical scienceLawEngineering

Abstract

fetched live from OpenAlex

For well over 12 years the Human Sexuality Program within Social Work Services of the Toronto District School Board has been serving lesbian, gay, bisexual and/or transgender (LGBT) students, teachers, parents and their families. Alongside individual, family and group support to the LGBT communities in the board, the program has also been delivering anti‐homophobia workshops to classrooms across the district from grades 1 to 12. At the classroom level, there has been a tremendous demand from teachers and schools seeking to fulfill their obligation under the school board's equity policy to create and maintain safe, welcoming and inclusive learning environments for LGBT students and students with LGBT parents. In the past two years much of the demand has come from teachers in the elementary panel, grades one to eight. This paper will discuss one aspect of the classroom work done in elementary schools, focusing on the students written responses to the anti‐homophobia presentations.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0110.003
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0720.022

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 head0.023
GPT teacher head0.359
Teacher spread0.336 · 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

Citations11
Published2004
Admission routes1
Has abstractyes

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