“Hard to crack”: Experiences of community integration among first- and second-generation Asian MSM in Canada.
Bibliographic record
Abstract
Asians are the largest racial minority in Canada making up 11% of the population and represented over 60% of new immigrants between 2001 and 2006. We examined the experiences of community integration for first-generation (n = 27) and second-generation (n = 22) Asian Canadian men who have sex with men (MSM) in their ethnic and gay communities. Through focus group interviews, we explored their level of connectedness and the level of discrimination they experienced in the two communities. Findings indicate that Asian MSM in general perceived their ethnic community as homophobic, stemming from a combination of seeing sex as taboo, stereotypes about being gay, and the affiliation with religion. Although the literature indicates that immigrants rely on the support of their ethnic communities, our finding suggest that this is not the case for Asian immigrant MSM, who in our sample reported feeling less connected compared to their second-generation counterparts. For the gay community, our sample reported mixed experiences as some regarded it as welcoming, whereas others described it as racist. However, these experiences did not differ by generational status. Many were aware of explicit messages stating "No Asians" in dating contexts, while at the same time being aware that some older White men were interested in dating Asians exclusively. Barriers to integration in both communities may contribute to feelings of isolation. Theoretical implications are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".