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Record W4407783311 · doi:10.1080/00918369.2025.2460988

Normalizing Sexual Orientations, Gender Identities and Expressions, and Sex Characteristics at the Global Level, from a Canadian Perspective

2025· article· en· W4407783311 on OpenAlexafffundabout
Mathieu Seppey, Gabriel Girard, Christina Zarowsky

Bibliographic record

VenueJournal of Homosexuality · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversité de Montréal
FundersFonds de recherche du Québec
KeywordsPerspective (graphical)PsychologySexual orientationGender identitySocial psychologyGender studiesGender schema theoryHomosexualityDevelopmental psychologySociologyMathematicsPsychoanalysis

Abstract

fetched live from OpenAlex

By developing its first Feminist International Assistance policy, Canada has positioned itself as an international feminist and diverse SOGIESC rights leader. However, the scarcity of references to sexual orientations, gender identities and expressions, and sex characteristics (SOGIESC) has raised questions on how these concepts were included in such a policy. This case study's objective is to better understand how Canadian policies play a role in including and normalizing diverse SOGIESC at the global level. We used documentary research, observations, and interviews to respond to that question. An abductive analysis was conducted, integrating a socio-ecological approach with emerging themes from the data. All socio-ecological levels were mobilized by Canadian actions toward SOGIESC normalization. Public policies were informed by a human rights-based approach and inclusive language. Canadian norms toward SOGIESC rights were conveyed within international communities by building bridges, positioning Canada as a political broker, while organizational resources remained limited. Individuals and their interpersonal skills were central in creating allyship through firsthand experiences. The importance of transpartisanship and stronger coordination of soft power emerged as new and practical strategies responding to inclusion and normalization challenges. These strategies could represent important interactive spaces and leaders, in a context of rising conservative right-wing coalitions.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score1.000

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 studies0.0020.000
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 head0.053
GPT teacher head0.360
Teacher spread0.307 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

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