Teachers constituting the politicized subject: Canadian and US teachers’ perspectives on the ‘good’ citizen
Bibliographic record
Abstract
This study examines how secondary history teachers in the United States and Canada understand their role in promoting citizenship and national identities. Building upon Anderson’s concept of ‘imagined communities’, I argue that compulsory history classes are key sites for imagining the nation and communicating norms about citizenship. While the citizenship education literature has begun to explore teachers’ beliefs about citizenship, researchers in the fields of citizenship education and history education have not examined how history teachers understand the ‘good’ citizen or the place of their subject in forming national identities. I interviewed thirteen secondary history teachers (seven US/six Canadian) to examine their beliefs about citizenship and national identity. I sought to understand how they engage with broader discourses about citizenship and the nation. Twelve of the thirteen teachers described the good citizen in ways consistent with Westheimer and Kahne’s models of the personally responsible citizen and the participatory citizen. US teachers also expressed a desire to foster students’ individual judgement and critical thinking skills, whereas Canadian teachers stressed the importance of fostering national identity as well as students’ responsibility to the collective good.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.073 | 0.033 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".