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Record W7079480165 · doi:10.26108/xn26-en48

Broken promises: a content analysis of Nova Scotia institutions of higher education's campus sexual assault policies

2023· article· en· W7079480165 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2023
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaLegislationSexual assaultSexual violenceContent analysisResource (disambiguation)Policy analysisSexual abuse

Abstract

fetched live from OpenAlex

Sexual violence is a widespread issue on university campuses in Canada, where one in five female undergraduate students are victims of sexual assault. Despite decades of research, the statistics have not improved, highlighting the need for effective anti-violence legislation and policies that are properly informed, implemented and enforced. This thesis employs a content analysis of the sexual violence prevention policies of ten English-speaking Nova Scotia universities in relation to recommendations made by the Provincial Sexual Violence Prevention Committee. The study draws from two theoretical perspectives, Beverly McPhail's Feminist Framework Plus and the Information-Motivation-Behavioural Skills model as applied to consent by Shumlich and Fisher. The findings show that none of the universities are meeting the targets they have committed to in their policies, highlighting the need for increased resource allocation and authoritative policy evaluation strategies to effectively address sexual violence on university campuses.

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)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.694

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.008
Science and technology studies0.0050.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.320
Teacher spread0.239 · 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 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
Published2023
Admission routes1
Has abstractyes

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