Bibliographic record
Abstract
A persistent and troubling trend in teacher education programmes is how gender is constructed heteronormatively. Finding ways that challenge novice teacher thinking about gender and gender identities has proven to be difficult ([Grace, A. P., and K. Wells. 2006. “The Quest for a Queer Inclusive Cultural Ethics: Setting Directions for Teachers' Preservice and Continuing Professional Development.” In New Directions for Adult and Continuing Education, edited by R. J. Hill, 51–61. San Fransisco: Jossey-Bass.; Kitchen, J., and C. Bellini. 2012. “Addressing Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ) Issues in Teacher Education: Teacher Candidates’ Perceptions.” Alberta Journal of Educational Research 58 (3): 444–460.]). This article describes a recently completed study in which Mail Art and autoethnographic writing were used to disrupt normative understandings of gender and gender expression. After detailing the study's theoretical foundations, three visual and textual exemplars illustrate how heteronormativity can be productively disrupted. The article ends with a list of potential questions for educators that might disrupt dominant, heteronormative educational practices.
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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".