Policy Learning from Canada: Reforming Scandinavian Immigration and Integration Policies
Bibliographic record
Abstract
Focusing on the three Scandinavian countries, Denmark, Norway, and Sweden, Policy Learning from Canada is a systematic study of the international relevance of the Canadian immigration and integration policy model. To reveal how the Canadian immigration model has shaped the reform process in Scandinavia, Trygve Ugland critically examines public documents, including government proposals, documents from parliamentary debates, and reports by ad-hoc expert commissions, as well as letters from consulted agencies. Ugland’s intensive studies on Canada’s immigration and integration policies depict Canada not only as a model and inspiration to Scandinavian policy makers, but, in particular, as an intellectual stimulus for the rediscovery of labour immigration in Scandinavia during the 2000s. The study demonstrates that the Canadian model, often perceived as a product of unique circumstances, can be relevant in other countries
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".