Regimes of belonging - schools - migrations : teaching in (trans)national constellations
Bibliographic record
Abstract
This edited volume presents international perspectives on the nexus of transnationality, schools and teacher education. It aims to critically discuss whether the national orientation of schools and teacher education is appropriate in light of increasing migration and transnationality. The contributions offer ideas from international teacher education research and school pedagogical practice in different nation-state contexts such as Austria, Canada, Chile, Greece, Israel, Japan, Switzerland, Turkey, the UK, and the USA. They all have in common that they are concerned with the question of which empirical and theoretical approaches are suitable for describing the phenomena of pedagogical-professional dealings with migration-related and transnational demands on schools found in the field of schools and teacher education. In raising this question, they do not reduce the analytical focus on migrants, whatever is meant by this expression, and their migration paths, actions or attitudes. Instead, the authors analyse the global interconnectedness and entanglements – each embedded in their specific national and global societal power structures and hierarchical relationships – and the country-specific and transnational structures and contextual conditions of schools and teacher education. These structures and conditions affect all school actors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".