Feminist Care and Being Tough Enough: An Interview with Michelle Forrest
Bibliographic record
Abstract
This article takes the form of an interview with Dr. Michelle Forrest. A philosopher of education, a teacher, a feminist, and a mentor to many, Michelle has been a longtime member of the Canadian philosophy of education community. This interview, conducted by her colleague, Adrian Downey, and her PhD student, Renée McKinstry, looks back over Michelle’s work in philosophy of education, offering her the chance to reflect on her contributions considering the changes in educational thinking and social circumstance throughout her career. Specifically, Michelle discusses her dissertation on pedagogical openness and the openness of the text, the feminist ethics of care and feminist irony, the dangers of comparative thinking, coloniality, and the significance of the Canadian Philosophy of Education Society (CPES) to her career and life as a philosopher of education. The interview concludes with Michelle’s advice to future scholars working the foundations of education and especially philosophy of education.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.017 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".