Bibliographic record
Abstract
Worldwide, migration is a human condition which threatens as much as it preconditions social development. Modern industrial societies attempt to politically deal with the issue of human mobility through immigration policies. These policies seek to control borders, regulate the relationship between the migrants and the state, and have to deal with aspects of diversity: e.g. minority formation, ethnic identity, and culture. The United States, Canada and Sweden are often cited as prototypical examples of old and new immigration countries, implying either that Europe should look to North America for examples or, conversely, that Europe's 'problems' with immigration are so new and unique that 'we' have to seek 'our' own, i.e. culturally specific, solutions. By comparing the historical development of policies in the U.S., Canada and Sweden, the essay challenges the concept of 'old' versus 'new' immigration countries. Neither have old immigration countries been 'naturally' open to immigration nor is immigration a new phenomenon in the European context. Rather, all societies have long, and often conflictual, histories of negotiating issues of migration and diversity (Hoerder, et al., forthcoming).KeywordsLabor MarketImmigrant WomanAsylum SeekerImmigration PolicyMigrant WomanThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".