Bibliographic record
Abstract
I argue that philosophy has a dual role in teacher education: first, it prompts teachers to take individual responsibility for and become more reflective about the values expressed by their teaching practices so as to enable them to teach with greater authenticity; second, it provides teachers with a disciplinary technique that is useful in the facilitation of student reflection and dialogue so as to enable students to think and live more authentically. In this paper, I focus on the former and suggest that because teaching practices are expressions of values, teachers need to become more aware of competing conception of the human good(s)—including their own—and how these inform their relationship to disciplinary expertise, educational institutions, and teaching. I argue that authentic teaching necessitates: a conviction that individuals are improved, as human beings, by what it is they study; a deepening engagement with what this conviction means; and a commitment to its truth by way of how one engages with one’s discipline and students. It is in this regard that I explore Plato’s dialogue Gorgias, in particular, the example of Socrates, his conversations with Callicles, as well as his distinction between sophistry/pandering and educating/healing. In the final part of the paper, I argue that, assuming I am correct about the necessity and value of teaching authentically, philosophy—conceived of as honest, rigorous, ongoing, open-ended and dialogical engagement with our convictions—should be an integral part of any good teacher education program.
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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 | 0.057 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.012 | 0.145 |
| Scholarly communication | 0.025 | 0.036 |
| Open science | 0.005 | 0.023 |
| Research integrity | 0.016 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 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".