Understanding Sexual Minority Male Students' Meaning-Making About Their Multiple Identities: An Exploratory Comparative Study
Bibliographic record
Abstract
This exploratory comparative study examines the meaning-making experiences of six sexual minority males attending college or university in Canada or the United States. All of the participants identified as sexual minority males who were cisgender, out to family and/or friends, and between 20 and 24 years of age. In particular, the participants spoke about the intersections between their race, gender, and sexual orientation as salient aspects of their multiple identities. Using a blend of qualitative methods, including case study, phenomenology, and grounded theory, I identified four themes that emerged from the data: (1) engagement in a social justice curriculum; (2) involvement in LGBT student organizations or resource centres; (3) experiences of discrimination and dissonance; and (4) engagement in reflective dialogue. I discuss the implications of these themes for professional practice and future research.
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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 | 0.000 |
| 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) | 0.002 | 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 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".