Gendered Perceptions of Place on York University's Keele Campus through a Lens of Personal Safety
Bibliographic record
Abstract
The York University Keele Campus is a public space that is primarily used by students, faculty, and staff and at any given moment there can be thousands of individuals on the University campus. With a student population of just over 50,000, York University is one of the largest universities in Canada and resembles a small city. Much like a city, the Keele Campus of York University has been impacted by incidents of sexual assault, robberies, hate crimes and criminal activity that have produced caution amongst those who interact with the Campus. The incidents that have occurred on the Campus have affected many individuals ability to establish a sense of place and cause them to restrict their use of space. On a university campus where incidents are publicized by the socialization between students, media reports, and notification emails, concerns regarding personal safety manifest into perceptions of place that are highly gendered. Through a lens of personal safety, this thesis seeks to understand students perceptions of place on the Keele Campus, identifying how the built environment, students gender identity, and the reputation attributed to space contribute to students perceptions. Moreover, it will explore how the perceptions of place held by students affect their daily geographies of the Keele Campus and challenge the gender normative direction of the Crime Prevention Through Environmental Design model that exists in the governing and operation of the Keele Campus.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
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".