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Record W4409546796 · doi:10.1080/00918369.2025.2489454

Lateral Gender-Based Violence in 2SLGBTQ+ Communities: The Stifling of Queer Joy Through Intersectional Oppression, “Pitiful” Sexuality Education, and Media (Mis)Representation

2025· article· en· W4409546796 on OpenAlexafffundabout
Jessica Wright

Bibliographic record

VenueJournal of Homosexuality · 2025
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsMacEwan University
FundersPublic Health Agency of Canada
KeywordsHuman sexualityOppressionQueerGender studiesSociologyRepresentation (politics)IntersectionalityHeteronormativityPolitical science

Abstract

fetched live from OpenAlex

There is a gap in the field of gender-based violence concerning lateral violence within 2SLGBTQ+ communities. This paper helps fill that gap by offering participants' narratives from The Queer Sexual Joy Project, which engaged 100 2SLGBTQ+ youth from Canada and the US, ages 18-35, in focus groups, participatory visual arts-based research, one-on-one interviews, and surveys. The study provides insight into how lateral violence is fueled and expressed through overlapping and intersecting systems of oppression, including fatphobia, transphobia, sexism and misogyny, racism, and ableism. Participants' experiences also highlighted that while lateral violence reduces the potentialities of queer sexual joy, this violence is catalyzed and reproduced through troubling depictions of 2SLGBTQ+ communities in popular media and sexuality education. The paper calls for further research on lateral violence and for increased and diverse representation of 2SLGBTQ+ communities in media and education to help address the disproportionately high rates of gender-based violence in these communities.

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)0.002
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 score0.033
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.445
Teacher spread0.362 · 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

Citations3
Published2025
Admission routes3
Has abstractyes

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