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Record W4256321019 · doi:10.31542/r.gm:1836

Genuine concern or lip service: sexual violence policies in Canadian post-secondary institutions

2019· dissertation· en· W4256321019 on OpenAlexaboutno aff
Kelsey Friesen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSexual violenceContext (archaeology)LegislaturePublic relationsPolitical scienceCriminologyCriminal justicePsychologyLaw

Abstract

fetched live from OpenAlex

Post-secondary institutions are intended to be safe spaces where students, faculty, and staff are encouraged to experience and engage in critical thought and discussion. When critical thought and discussion occurs, it may raise awareness, give context, and challenge assumptions which have potential to shift the narrative around big issues. Although post-secondary institutions foster the intellectual growth of its members, they are also environments where its members face sexual violence. While sexual violence has always been present in these institutions, it is only more recently that sexual violence along with its impacts on victims received closer attention from media. This media attention resulted in a public pressure which demands post-secondary institutions to create and implement policies and educational programming that specifically addresses sexual violence. Other policies and processes, however, such as Student Codes of Conduct the criminal justice system, already designate forms of sexual violence as intolerable or illegal. Due to the massive public pressure and demand for policies which specifically address sexual violence and sexual violence only, it is crucial to examine how or if these policies add or contribute to the policy or legislative context in Canada. To examine these policies, this research investigates campus community members’ knowledge of and perceptions of sexual violence policies in the context of Canadian post-secondary institutions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.062
GPT teacher head0.386
Teacher spread0.324 · 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
Published2019
Admission routes1
Has abstractyes

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