Considerations of Identity in Teachers' Attitudes toward Teaching Controversial Issues under Conditions of Globalization: A Critical Democratic Perspective from Canada
Bibliographic record
Abstract
Controversy, as a vital principle of democracy, plays a central role in education for critical democratic global citizenship. Controversial issues, however, raise pedagogical challenges for teachers in that they are not only explicitly political, but also potentially threatening to the reproduction of status quo ideals and embedded national narratives – themselves keystones of citizenship education. The findings from this dissertation study report survey data on teachers’ attitudes toward teaching controversial issues from 202 Canadian teachers, as well as findings from interviews conducted with 16 Alberta teachers about how their multiple identities, and those of their students, intersect with their attitudes toward teaching controversial issues. The findings are discussed against indicators of critical democratic global citizenship education (CDGCE) which I advance in the thesis following from my investigation into the relationship between critical theory of a) democracy, b) globalization, and c) education. I engage the findings through the lens of critique and possibility and the reproduction and interruption of hegemonic discourse. Read through this lens, I found that hegemonic discourses of neutrality and universalism are being both reproduced and interrupted in complex ways that do affirm, but mostly refute, the promise of education for deepening democracy under conditions of globalization. Discourses of neutrality and universalism are being reproduced through insidious practices that affirm difference-blind and blank slate ideals and these need responding to. These have implications for how students in Canadian classrooms may be being prepared for critical democratic global citizenship education. Despite the misguided emphasis on the danger of teachers’ expressing extreme views in dominant discourses of education that question the place of controversial issues in school, I argue that the greater threat to deepening democracy is not teachers who express extreme views; it is curriculum and teachers who do not question familiar ones. In turn, I call for critical discursive and reflexive practices for teaching and learning with controversial issues that foreground identity, difference, and feelings as explicit material for learning. Finally, I delineate specific recommendations that are crucial responses for realizing the promise of education for deepening democracy under conditions of globalization.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.073 | 0.020 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".