Bibliographic record
Abstract
In the context of immigration and settlement, Canada and Germany are often portrayed as opposites: Canada represents a settler society and Germany an ethnic nation. The different approaches and attitudes of the two countries towards immigration can be linked to different historical understandings of nationhood. Canada could not be imagined as a country without its immigrants; immigration is an integral aspect of national identity. Conversely, although Germany has always received immigrants, national identity has historically been conceived in ethnic terms. In this paper, I explore some of the contradictions in Canadian and German immigration debates related to national belonging. For example, Canada’s identity as a settler society has long marginalized Indigenous populations, while in German debate the narratives of ethnically-belonging Germans and newly-arriving migrants openly engage with each other. By exploring these contradictions, I develop a perspective of the dialectic of migration and ethnic belonging that can be applied to both Canada and Germany.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.065 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".