Revisioning curriculum in the age of transnational mobility: Towards a transnational and transcultural framework
Bibliographic record
Abstract
Under the new mobilities paradigm migration is conceptualized as circulatory and transnational, moving us beyond the framework of methodological nationalism.Transnational mobility has called into question dominant notions of migrant acculturation or assimilation.Migrants no longer feel obligated to remain tied to or locatable in a "given", unitary culture.Rather, they are becoming embedded within a shifting field of increasingly transcultural identities.While migrants are becoming more transnational and adopting fluid, transcultural identities, there is a lack of focus and engagement with transnationalism as well as transculturalism in the official Canadian public school curricula.As scholars contend, Canadian school curricula are still based on Eurocentric, homogenizing, nationalistic discourses that tend to normalize values, norms, and behaviours that are perceived as "different" from the dominant norm.In response to the limitations of Canadian official curricula, as noted by various scholars who have examined curriculum documents, this essay proposes a revision of Canadian curricula in the context of transnational mobility with the aim of developing an approach that would integrate transnational and transcultural perspectives into the existing system.The article thus proposes a transnational and transcultural framework as an alternative to build a more ethical and inclusive school curriculum in Canada.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".