Bibliographic record
Abstract
The term ‘rape culture’ was coined in the 1970s by American feminists, to describe a culture of intimidation whereby male aggression toward women is both normalized and encouraged (Buchwald, Fletcher, & Roth, 1993). This honours project explores rape culture transmitted via an online medium at a Canadian university campus. Despite over 40 years of addressing sexual assault in Canada, research continues to show that approximately 20%-28.5% of Canadian undergraduate females are sexually assaulted during their four-year degree (Krebs, Lindquist, Warner, Fisher & Martin, 2009, p.643; Newton-Taylor, DeWit, & Gliksman, 1998, p. 156; Suran, 2014, p. 274). This is especially concerning since, in comparison, police reporting of sexual assault was at 5% in 2014 (Perreault, 2015, p. 25) and on-campus reporting consisted of only 700 documented cases from 87 Canadian universities and major colleges, between 2009 and 2013 (CBC News, 2015). Only since 2014 have universities and colleges begun to openly acknowledge the need for such policies and protocols (Mathieu, 2014, para. 6). The focus of this Honours project is to examine the student-led Facebook page “MRU Confessions” that is directed towards Mount Royal University students in Calgary, Alberta. Using a content analysis approach, the aim is to examine how, and to what extent media facilitates or challenges campus rape culture. Although this project is exploratory in nature and focuses on only one Canadian campus, it provides a basis from which other studies exploring rape culture on university campuses can emerge. Ultimately, this project aims to invoke discussion and increase awareness concerning rape culture while providing commentary to the development of a national framework that universities can use in shaping policy, programs, and education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".