Understanding the intersecting identities of Asian immigrant LGBTQ+ youth and young adults and their needs in mental health and social support services
Bibliographic record
Abstract
Asian immigrant LGBTQ+ youth hold multiple marginalized identities.Though literature specific to their experiences is sparse, disparate veins of research suggest that these youth may contend with a variety of challenges, with negative consequences for their mental health and wellbeing.As previous research with immigrants, visible minorities, and LGBTQ+ youth suggests that each group encounters distinct issues in using mental health and social services, it is possible that Asian immigrant LGBTQ+ youth may face all of these barriers simultaneously, and that these barriers may intersect to shape a novel experience within such services.The contemporary knowledge gap with regards to this group is particularly worrisome in Canada: statistics indicate that large populations of Asian immigrants reside in the three most populated cities and, considering baseline rates of non-heterosexuality and transgender identities, it is likely that the needs of many Asian immigrant LGBTQ+ youth in these cities are not being adequately met.To help address this knowledge gap, a qualitative study was conducted to examine the interactions between their identities and explore their experiences within mental health and social support services.Semi-structured interviews were completed in Montreal with 10 young adults identifying with the group in question and six service providers that provide services relevant to these youth.Interviews were transcribed and thematically analyzed.Results illustrate that on the one hand, Asian immigrant LGBTQ+ youth negotiate challenges with their family related to their sexual and/or gender identity, suffer alienation in various domains of their lives, and use a variety of coping strategies to deal with these experiences.On the other hand, they also expressed appreciation for the positive aspects of their lives.Service providers and young adults identified a number of weaknesses and possible improvements in mental health and social support services in relation to serving Asian immigrant LGBTQ+ youth.Obtaining ethical approval for this study shed light on issues that may hamper research with racialized LGBTQ+ youth.These issues are explored in a second article by contextualizing them in the history of ethical review processes and discussing the dilemmas faced in the process of conducting this study with Asian immigrant LGBTQ+ youth.Finally, avenues of change are explored to promote research with racialized LGBTQ+ youth.Though words cannot adequately capture my gratitude for the immeasurable support I've received throughout my Master's training, I will attempt to convey an inkling of my appreciation here.First, I would like to convey my sincere gratitude to my supervisors, Dr. Lucie Nadeau and Dr. Srividya Iyer.The support and guidance they have provided me over the past two years and the time and resources they have invested in ensuring this project came to fruition are a true testament to the power of allyship in the scientific discipline.They validated my efforts and struggles for the duration of the program, and challenged me to think about issues that emerged in my project in more complex and respectful ways.I know these new perspectives and insights will be an incredible asset to my future aspirations.Thank you to Dr.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".