Educational Judgment: Linking the Actor and the Spectator
Bibliographic record
Abstract
The difficulty of connecting the knowledge generated by educational researchers and the practice of classroom teachers is familiar. Academics write about the importance of research for understanding and improving classroom practices; classroom teachers dismiss the academics’ research knowledge as a poor substitute for actual experience. We argue for moving from debates between spectators and actors about knowledge and practice to discussions about how all educators can foster good judgment. We outline two major accounts of judgment in Western thought, Aristotle’s and Kant’s, which ultimately privilege the spectator over the actor. We then introduce the work of Hannah Arendt, who linked thinking and acting without privileging either in her conception of judgment. Focusing on how teachers and researchers might become better educational judges is a crucial, yet neglected, agenda that promises to link these communities.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.096 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.008 |
| 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".