The History Classroom as Site for Imagining the Nation: An Investigation of U.S. and Canadian Teachers' Pedagogical Practices
Bibliographic record
Abstract
This multiple case study compares the enacted history curricula in one U.S. and one Canadian school district in order to understand how high school teachers engage in the construction of national identities and the conceptualization of the “good” citizen. Following Anderson’s (1991) concept of nations as “imagined communities,” compulsory history classes are key sites for imagining the nation. Within the context of contemporary processes of globalization, the study explores the process of imagining the nation within a global “social imaginary” (Rizvi & Lingard, 2010). Data sources include interviews with seven teachers in the U.S. state of Maryland and six teachers in the Canadian province of Ontario; classroom observations of five of those teachers; classroom artefacts; and local, state, and provincial curriculum documents.\nExisting empirical research has devoted little attention to the specific historical narratives that are used to tell the nation’s story. Wertsch’s (2002) concept of narrative dialogicality provides a useful framework for understanding how narratives act as cognitive tools to distribute collective memory throughout a social group. Classroom observations focused on the study of World War II in required high school history courses. In telling the story of the nation, teachers used historical narratives that ran counter to popular images of their respective nations. Despite Canada’s image as a “peacekeeping” nation, triumphal military narratives dominated the Canadian classes. Conversely, in the United States, the world’s dominant military power, political narratives dominated, with military narratives playing a supporting role.\nIn enacting the curriculum, teachers negotiated neoliberal policies of accountability in various ways. For the Maryland teachers, the level of surveillance was more intense due to locally developed standardized course examinations, resulting in very limited autonomy for curriculum development. The Ontario teachers also reported increased surveillance of their work, but they retained a high degree of professional autonomy. In keeping with previous research, there were notable differences between the curriculum experienced by students from high and low socioeconomic status 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 | 0.011 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".