Shifting Individuals and an Organization Towards Social Justice: A Teacher Education Program Imperative
Bibliographic record
Abstract
Globalization is the interconnected national and international forces that shape and define nations, economies, and peoples and that extend to schools. Higher education institutions, and kindergarten to Grade 12 school systems, are impacted by the internationalization of teaching, research, and service in response to market- and ethically driven discourses of targeted international admissions policies. Teacher education programs are positioned to respond to the internationalized teaching and learning context to support nondominant teacher candidates and prepare future teachers for diverse classrooms post-graduation. This OIP problematizes an inconsistent strategic direction to prioritize culturally sustaining pedagogies in a diverse teacher education program located in British Columbia, Canada. It draws from the theoretical concepts of critical epistemology and organizational identity as foundational drivers of change and incorporates concepts of intercultural competency development and culturally responsive pedagogies as evidence-based models to guide improvement plans. A social justice–oriented plan executed through a transformative leadership approach at both the macro and micro change levels creates the structural foundation for this OIP. Appreciative and collaborative inquiry offer all stakeholders’ participatory access points to amplify nondominant voices in the change process. A generative, multimethod integrated monitoring, evaluation, and communication plan supports this foundational change through a learning approach. The outcome connects theory to practice for stakeholders to promote unlearning and prioritize the decolonization of teacher education as liberation for nondominant students.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.027 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".