Strengthening Equity and Inclusion in Urban Greenspace: Interrogating the Moral Management & Policing of 2SLGBTQ+ Communities in Toronto Parks
Bibliographic record
Abstract
There is growing recognition that greenspace provides invaluable benefits to health and wellbeing, and is essential infrastructure for promoting both social and environmental sustainability in urban settings. This paper contributes towards efforts to build 'just' and equitable urban sustainability, and more specifically greenspace management, by drawing attention to hostility and exclusion experienced by two-spirit, lesbian, gay, bisexual, transgender, queer, genderqueer, pansexual, transsexual, intersex and gender-variant (2SLGBTQ+) park occupants. There is evidence that access to greenspace is inequitable-despite ongoing media accounts of targeted violence and discriminatory police patrolling of 2SLGBTQ+ communities in urban parks, this population has not received adequate research attention. This paper examines systemic barriers that impede urban greenspace access among 2SLGBTQ+ communities, including how the threat of violence in greenspace limits opportunities for accessing benefits associated with naturalized settings. These themes are explored within the context of the City of Toronto, Canada. Our mixed-method approach draws upon key informant interviews, key document content analysis, and ground-truthing. Our findings reveal how queer corporeality, kinship and love subvert deeply entrenched heteronormative social values and understandings of sexuality, partnership, gender, and use of public space, challenging institutional understandings of morality and daily life. The paper concludes by reflecting on the state of 2SLGBTQ+ communities' relationships to greenspace, and potential ways forward in building greater inclusivity into the social fabric of park design and management.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.023 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".