Between Every “Now” and “Then”: A Role for the Study of Historical Agency in History and Citizenship Education
Bibliographic record
Abstract
This article reports on a review of research into students' reasoning about social change and causes they attribute to selected historical events. In this review, I distinguish studies into social change and causality as two methodological approaches to historical understanding before relating findings into the ways that students reason about agency in social change. I consider two of many possible explanations for these findings, one each from a cognitive and a social psychology perspective. I then turn to sociology for two articulations of agency as tools to enhance students' historical thinking and reflection on their variegated capacities as agents of social life: a) personal agency as nested moments of re-“iteration,” “practical evaluation,” and “projectivity” and b) historical agency as collectively expressed struggle over the ideals, images, and stories people use to reiterate a past in the present so as to imagine personal and social projects. I argue throughout that student attention in classrooms to assumptions about agents and agency used in historical explanations enhances both their historical explanations and capacities as citizens. Rather than citizens, however, I begin this article with a feminist argument that teachers address students first and foremost as agents.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.055 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".