Exploring Safe Spaces in On-Campus Residences: Perspectives of Black and Racialized Students Through Auto-Photography
Bibliographic record
Abstract
Understanding the experiences of Black and racialized students in on-campus residences is crucial, yet remains underexplored within Canadian higher education. This study employs auto-photography and photo-elicitation interview methods to examine the experiences of Black and racialized first-year students at the University of Waterloo, and to explore how on-campus residences can foster safe and inclusive spaces. Twenty participants contributed 234 photographs and 446 pages of interview transcripts. Thematic analysis revealed five overarching themes: The Intersection of Nature and Social Connections, The Importance of Connection in Creating a Sense of Belonging, Sense of Space and its Role in Well-Being and Academic Engagement, Equitable Living Spaces, and Covert Isolation. Findings highlight the role of safe spaces in promoting inclusion, well-being, and academic engagement, offering actionable insights for the University of Waterloo. This research contributes to the advancement of Equity, Diversity, and Inclusion (EDI) policies and practices within Canadian higher education on-campus living environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".