Refugee Crisis in North America: Comparative Case Study of the United States and Canada
Bibliographic record
Abstract
The US continues to lean toward a traditional, negative approach (Gomez, 2018) and to encourage cultural diversity in Canada. In their initial immigration legislation, the Canada and US shared profound resemblances: both began with Euro- and Christian-centered laws in order to limit the influx of migrants from Southern/Eastern Europe and Asia. The researcher has taken an empirical approach to a comparative methodology, and performed a study of the immigration policies of each country empirically. Both qualitative and also quantitative data analysis approaches were used for the present research. The findings of the research suggest that the two countries share some of the foundational similarities concerning their initial immigration law. For instance, this includes the inception of their policies with the base as Euro and Christian policies, where both attempted to achieve restricted migration flow from the Asia as well as Southern/Eastern Europe. However, with time, the changes in the migration policies have occurred due to the diverging socio-cultural as well as geographical aspects.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.025 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".