Rejection and Resilience in a “Safe Space”: Exploratory Rapid Ethnography of Asian-Canadian and Asian-American Men's Experiences on a Gay Cruise
Bibliographic record
Abstract
Similar to other leisure spaces, gay cruises allow for self-expression and development of community, but in potentially sexualized environments over comparatively prolonged periods. Understanding racialized gay men’s resiliency in these spaces is important to leisure theory and practice, yet it has received little empirical attention, with an existing gap regarding resilience strategies of racialized gay men. Informed by minority stress theory and resilience theory, I use rapid ethnography to explore experiences of Asian-Canadian and Asian-American cisgender gay men (n = 7) on a gay cruise. Thematic analysis highlighted the cruise as a “safe space” where participants felt liberated. However, participants discussed rejection based on race and body size in this “safe space.” To cope, participants drew on existing resources rather than creating new ones, speaking to their resources as “my friends are my oasis.” Findings contribute to understanding Asian gay men’s resiliency in leisure spaces, highlighting the importance of social resources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".