Growing up gay or bisexual: The experiences of young gay and bisexual men in Windsor and Essex County, Ontario
Bibliographic record
Abstract
This study explored the experience of forming a stigmatized cultural identity within a particular social and historical context, specifically, gay and bisexual male (GBM) identity in Windsor and Essex County, Ontario, Canada. Savin-Williams' (1998) trajectory model of sexual identity development with milestones was utilized and issues identified in the research literature and significant problems confronted by GBMs were included. Sexual identity first milestones included attractions, self-labelling, disclosure, sex, love, and romantic relationships. Issues included harassment, HIV/AIDS, homelessness, use of mood altering substances, depression and suicide, and the sex trade. A mixed quantitative and qualitative method, sequential explanatory design, was used to collect occurrence and age data on milestones and issues significant to the development of GBM identities through an online survey, followed by a semi-structured interview. The 79 survey respondents and eight interviewees were GBMs, ages 17 to 26, who had lived in Windsor and Essex county for at least half of their lives. The trajectory model (with some alteration of the ordering of stages due to the influences of social, interpersonal, and intrapersonal contexts) was found to be useful in capturing the general sexual identity developmental progression of participants, while highlighting variability in occurrence, age of achievement, and order. Many of the issues identified in the literature were experienced by varying proportions of participants, with harassment being the most common and related to comparisons with others. Interviewees' narratives, analyzed for descriptive interpretative themes, highlighted the particular context of Windsor and Essex County in the development of their sexual identities and participation in and becoming part of a sexual community.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".