Steps toward universalism in immigration policies : Canada and Germany
Bibliographic record
Abstract
Canada’s points system was historically significant for its universalism, ending ethnic discrimination in the selection process for new immigrants. In spite of its appeal world-wide, however, it has not been successful in matching well-qualified migrants to good jobs, instead leading to “brain waste”, as exemplified by academics driving taxis. To avoid this problem, Germany should not imitate Canada’s points system, but instead Canada’s easy naturalization, welcoming multiculturalism, and acceptance of immigrants in political life. Germany has made important steps toward a universalist immigration system. It is part of the EU’s open sphere, which enables every EU citizen to move freely. This sphere may be further widened in the coming years. Moreover, the EU Blue Card system enables anyone in the world to work in Germany, with only a minimum salary level as a condition. The EU’s open sphere and Blue Card system are making important contributions to the establishment of an open world, a perspective that should be discussed in North America. Keywords: points system, Germany, Canada, immigration, universalism, brain waste, EU, Blue Card, central planning, foreign students
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".