Coming In/Out Together: Queer(ing) schools through stories of difference and vulnerability
Bibliographic record
Abstract
Over the past few decades, Canada has implemented more equitable laws that delineate movement towards greater acceptance of gender and sexual minorities (e.g. Smith, 2008; Rayside, 2008). Despite these shifts, evidence suggests that public schools remain unsafe and non-affirming spaces for many people who identify as LGBTQ*. While efforts have been made to create safe(r) spaces for students who identify as LGBTQ*, primarily through anti-bullying policies, only a minority of Canadian schools have affirmatively recognized sexual and gender diversity in classroom learning. Some scholars assert that without accompanyingcurricular reform, anti-bullying work may promote a singular and dichotomized queer narrative: that to be LGBTQ* equates victimhood or resilience. This study — through a qualitative analysis of interviews with two English teachers, surveys from 30 Grade 10 students, and observations from a workshop with a Grade 10 class — explores the role of storytelling as a means for fostering queer-affirming spaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| 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".