Queer Eye on Inclusion: Understanding Lesbian and Gay Student and Instructor Experiences of Continuing Education
Bibliographic record
Abstract
Little is known about the experiences of lesbian and gay faculty and students in continuing education. In order to address this gap, this article introduces and discusses a research project conducted to understand the struggles and accomplishments of both lesbian and gay male faculty and students in continuing education (CE) in university settings. Six CE instructors and six CE students were recruited to participate in in-depth interviews from universities across western Canada. Using grounded theory for data analysis, two broad themes emerged: (a) CE in western Canada excludes lesbian, gay, bisexual, transgender, and queer (LGBTQ )content in their student and instructor orientation processes despite being placed in “progressive” institutions; and (b) safety concerns appear commonplace in such environments due to the heteronormative organizational culture of CE. Despite these drawbacks, study participants demonstrated strategies to minimize risk and find safety and support. Study findings suggest that CE review its work and learning structures to include queer-inclusive pedagogies and content.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".