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Record W3049703707 · doi:10.1177/1363460720947308

Willed ambiguity: An exploratory study of sexual misconduct affecting sexual minority male university students in Canada

2020· article· en· W3049703707 on OpenAlexaffabout
Viviane Namaste, Mark Gaspar, Sylvain Lavoie, Alexander McClelland, Emily K. Sims, Alex Tigchelaar, Christopher Dietzel, JD Drummond

Bibliographic record

VenueSexualities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsMcGill UniversityUniversity of TorontoConcordia University
Fundersnot available
KeywordsSexual misconductExploratory researchHarassmentHuman sexualityThematic analysisSexualizationPsychologyAmbiguityGender studiesCriminologyQueerConversationSociologyHarmSocial psychologyQualitative researchSocial science

Abstract

fetched live from OpenAlex

We offer exploratory reflections on the matter of sexual misconduct affecting sexuality minority male students by males in positions of authority in the university, based on interviews with eight sexual violence service providers and five men across Canada with lived experience, as well as information gathered through our recruitment work. Data were interpreted using thematic analysis. Our results indicate that there is a need to think through the specificity of sexual misconduct involving men in university settings. Several dynamics operate to perpetuate a willed ambiguity on this issue that allow abuses of power to go unchecked. These include difficulties in having a conversation on this topic, the sexualization of gay male culture, gender dynamics among gay men, ‘queer’ justifications, risks of social isolation, and financial precarity.

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)0.008
metaresearch head score (Gemma)0.021
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0630.023
Scholarly communication0.0100.003
Open science0.0040.012
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.092
GPT teacher head0.329
Teacher spread0.237 · 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
Published2020
Admission routes2
Has abstractyes

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