Bibliographic record
Abstract
Abstract The chapter addresses the development of epistemic cognition in history by merging the perspectives afforded by developmental studies of epistemic cognition and consciousness with the insights gained from the literature exploring the development of historical understanding and epistemically charged ideas such as evidence and historical accounts. Given the results obtained by studies attempting to assessing individual epistemic beliefs in history and teacher and student capacity to think historically, Maggioni proposes to interpret the instances of epistemic inconsistency and the challenges and limitations in developing the capacity to think historically that have been observed in light of the developmental psychology literature, and in particular of Kegan’s model of epistemic development. The chapter includes the identification of specific ideas and habits of mind that may act as stumbling blocks in the development of epistemic cognition in history and suggestions for pedagogical 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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.011 | 0.026 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".