Internationalizing Ontario K-12 Classrooms for Social Justice: A Transnational Feminist Pedagogical Approach
Bibliographic record
Abstract
The internationalization of educational curriculum (IoC) has been identified as a priority in K-12 education in Ontario, Canada and beyond. Yet, institutional and policy initiatives related to internationalization fail to provide practical examples and positive practices that could guide K-12 educators in designing potent internalized curriculum supporting diverse students. Internationalizing curriculum efforts in Ontario further fail to engage cultural, racial, gender, sexual and other inequalities organizing social life locally and globally. This study addresses the gaps by posing the following research questions: How can we effectively internationalize K-12 education committed to gender equity and social justice in Ontario? How could such internationalized curriculum further support teaching and learning that fosters non-violent identifications and social relations? To answer these questions, the study uses a multi-pronged data collection method anchored by three distinct, but related pursuits identified in education and globalization literature: 1) global ethnography; 2) curriculum design; and 3) cultural and media digital archives located across the world. Using this approach, the study finds that by connecting social justice education theories with transnational feminist theory and practice, and by utilizing internationally available audio/visual texts, as well as material culture, such as gendered clothing and other items preserved in archives located in South Africa, Nigeria, India, China, the United States, Canada, Iran, Hungary, and Macedonia, educators in Ontario can effectively imbue classroom curricula with internationalized content dedicated to social equality and gender justice. The dissertation offers two concrete examples of such internationalized curricula programs designed for the secondary school level and envisioned for possible congruence with upper-level courses such as Civics Education (CHV20) and World Issues: A Geographic Analysis (CGW4U). The proposed curricula engage K-12 students with concepts of engaged citizenship, and social, economic, and political challenges facing Canada and the world today, paying special attention to gender equity and women.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".