Microaggressions experienced by LGBTQ academics in Canada: “just not fitting in… it does take a toll”
Bibliographic record
Abstract
Given contemporary attention to diversity and inclusion on Canadian university campuses, and given human rights protections for sexual orientation and gender identity, it is tempting to believe that marginalization is a thing of the past for lesbian, gay, bisexual, transgender and queer (LGBTQ) academics. Our qualitative study (n = 8), focusing on everyday experiences rather than overt discrimination, documents numerous microaggressions, the often-unintended interactions that convey messages of marginality. With colleagues, students and administrators, participants reported isolation, tokenism, invisibility, hyper-visibility, dismissal, exoticization, and lack of institutional support. Maintaining constant vigilance and caution was taxing. The everyday microaggressions that lead to isolation and a sense of dis-ease in pervasively cisgender-normative and heteronormative institutions are very difficult to challenge, as they are not the kinds of experiences anti-discrimination policies and procedures are designed to address.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".