Immigration policy criteria: a comparative study between the \nUK and Canada
Bibliographic record
Abstract
Immigration is a part of many countries' history and one of the most important issues \nin the world. However, many political and public concerns about the numbers of \nimmigrants have been raised particularly by the start of the 20th century. \nThis study aims to explore the criteria that influence the Immigration Policy (IP), and \ninvestigates the nature of British and Canadian IP and compare the situation of diverse \nimmigrants groups with different policies and circumstances in both countries to \ndiscover what is has used as an excuse to decrease the IP and promoted negative \npublic opinion against immigrants. Therefore, theoretical literature, official statistics’ \nand some immigration national surveys have been utilised. The research conclusion \nindicates that the political factor mainly and public sentiments are affecting negatively \nthe British IP, while Canadian IP has responded well to the economic needs, what has \nimpacted positively public attitude, in spite of the political influence is still clear to \nsuch extent.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".