Canada’s Immigration Policy, Moral Obligations and Global Justice
Bibliographic record
Abstract
In this paper, I defend Canada’s nationalist approach to immigration because it allows Canadians to exercise control over their national priorities and the future direction of their political community. Canada’s nationalist approach also allows Canadians preserve their national identity and the resourcefulness that it engenders. I base my arguments primarily on John Rawls’ claims that reasonable people, interested in furthering their individual interests, want to live in a society in which they can cooperate with other members of the society in a manner that is, largely, agreed upon and accepted by all members. On this basis, members of the society are willing to establish and abide by mutually agreed upon principles of justice to guide the assignment and distribution of rights, advantages and obligations within their society (ToJ 150-156). I also argue that, while the loss of skilled professionals to emigration can be beneficial, immigrants who originate from LDCs owe obligations to those left behind.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".