Seeking the cosmopolitan teacher: internationalising curricula in a Canadian preservice teacher education program
Bibliographic record
Abstract
This paper takes the trans-nationalising conditions of global mobilities, hyper-connectivity and super-diversity as bases for the internationalisation of teacher education (ITE) curricula and for ‘seeking the cosmopolitan teacher.’ We ground our conception of the cosmopolitan teacher in one novel Canadian exemplar of ITE in which we participate as curriculum developers and teacher educators. In the literature on ITE we find an overlapping set of rationales for, and notions of, the cosmopolitan teacher that link up to our own ITE context. However, still sparse in the literature are details on ITE curricula, which is our primary focus in the presentation of our exemplar. Our seeking the development of the cosmopolitan teacher aligns with the concept of ‘cosmopolitan learning’ (CL), which aims to deepen learners’ critical reflexivities of their situatedness within historically produced global interdependencies. Our paper illustrates how our ITE curricula provoke the ‘epistemic virtues’ of CL, to support further inquiries into ITE curricula and teaching, as a more pro-active, education-focused internationalisation.
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 | 0.002 | 0.004 |
| 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 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".