Making It Better for Lesbian, Gay, Bisexual, and Transgender Students through Teacher Education: A collaborative self-study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Teacher education programs have a critical role in helping incoming teachers develop a deeper understanding of lesbian, gay, bisexual, and transgender (LGBT) issues and their moral and legal obligations to counter homophobic bullying. In this self-study, two educators – a university professor and a classroom teacher, who facilitated a workshop titled “Sexual Diversity in Secondary Schools” in a faculty of education in a mid-sized Canadian city – reflect on the feedback provided by teacher candidates on workshop evaluation forms in relation to their experiences as teacher educators delivering the workshops. In particular, they consider (1) their commitment to this work; (2) why they taught the way they did; (3) the impact their approach had on teacher candidates in the workshops; and (4) what the study revealed about their teacher education 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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it