Practical epistemology of history teachers and its relationship to normative injunctions
Bibliographic record
Abstract
Over the past few decades, significant work has been done regarding the epistemic beliefs of history teachers. However, nuanced epistemic beliefs do not appear to manifest as regularly as may be expected in teaching practices (Wilke et al., 2022). While exploring the normative injunctions imposed in part by the hidden curriculum (Giroux & Penna, 1979), the “school form” (Barthes & Alpe, 2018), and the challenges that history teachers face, this article argues that explicit and implicit demands made on history teachers generate a form of practical epistemology, which goes beyond epistemological beliefs. While at times this appears at odds with their understanding of history as a discipline, it enables them to meet the diverse mandates and directives they encounter. We believe that the concept of practical epistemology (Gholami, 2017) provides avenues for reflection that deserve to be pursued. Lastly, regarding criterialist epistemology (Maggioni, VanSledright, & Alexander, 2009) and historical thinking (Seixas & Morton, 2013), we emphasize that they themselves could be subjected to a critical review by both students and teachers in their practice.
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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 | 0.020 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.079 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".