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Record W2761446748

Unwilling or Unequipped? A Case for Mandatory Training on Sexual Orientation and Gender Identity in Teacher Education

2017· article· en· W2761446748 on OpenAlexaffabout
Amelia Thorpe

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSexual orientationCurriculumBachelorTransgenderIdentity (music)QueerSexual identityPrejudice (legal term)HomosexualityDiversity (politics)PedagogyHeteronormativitySexual minorityPsychologyGender identityHeterosexismGender studiesSociologySocial psychologyPolitical scienceHuman sexuality
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the dearth of curriculum regarding sexual orientation and gender identity in teacher education programs across Canada. There is a dire need for curricular, linguistic, and structural change in order to ensure the recognition and protection of gender and sexual minorities in schools. Often, teachers cite a lack of knowledge around language and issues related to queer and trans identities as reasons why they are hesitant to teach related topics or support activism in their schools. An examination of curriculum related to gender and sexual minorities offered in Canadian Bachelor of Education programs will show how queer and trans identities are systematically delegitimized and explore why many teachers are ill-equipped to support these students. This paper calls for education programs to work towards the implementation of mandatory competencies that will encourage pre-service teachers to explore issues of gender and sexual diversity and provide a strong foundation to discuss these issues in productive, inclusive ways while problematizing the heterosexist and cissexist structures that shape educational institutions. Giving teachers the tools and knowledge to discuss sexual orientation and gender identity will allow them to better support students, develop and deliver inclusive curriculum, and address issues of discrimination and prejudice.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.197
GPT teacher head0.431
Teacher spread0.234 · 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.

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

Citations0
Published2017
Admission routes2
Has abstractyes

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