Bibliographic record
Abstract
In 2005, Canadian scholars Carol Schick and Verna St. Denis published an article entitled “Troubling National Discourses in Anti-Racist Curricular Planning.” In it, they describe encountering the same problems in their respective practices with pre-service teachers when addressing Indigenous and post-colonial curricula; namely, resistance. The authors identify four key areas of resistance offered by pre-service teachers: 1) there is a perception of loss of liberty in course selection when a required anti-racist course is mandated; 2) students perceive an affront with the possibility that they are morally lacking in some way that necessitates a course about the “other”; 3) most pre-service teachers do not see themselves as teaching aboriginal students and think they don’t need to learn about aboriginal people; and 4) students are afraid of feeling uncomfortable about the conditions of the “other” and their own implication in that power structure. The authors address these concerns through an autobiographical assignment that locates students within the matrix of political, historical and cultural power structures in Canada. In a precursor to their 2005 article, Schick and St. Denis (2003) published a similar treatise in the Alberta Journal of Educational Research entitled “What Makes Anti-Racist Pedagogy in Teacher Education Difficult? Three Popular Ideological Assumptions,” in which they provide anecdotal evidence of pre-service teacher resistance. Taken together, these two articles point to an important and difficult arena in the process of opening dialogues around post-colonial power relations embedded in the narratives of Canadian identity. As a Métis woman working in the field of education, I am particularly interested in expanding this dialogue to resolve the tensions the authors describe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.055 | 0.090 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".