The Social Landscape of Canada and Europe with Focus on Immigration Policies in the 21 <sup>st</sup> Century
Bibliographic record
Abstract
Abstract The article explores the social landscape of Canada and of the European Union (EU) with a focus on immigration and the social integration of immigrants, of asylum seekers or of persons seeking other forms of international protection due to their persecution, racial, religious, national grounds, holding political opinions, belonging to a social group in their countries. The article aims to analyse the policies of Canada and the EU in implementing the criteria of the Geneva Convention on the Status of Refugees (1951), into their policies and legislation. The research results show that Canada’s approach to immigration in the twenty-first century reflects its longstanding identity as a country of immigration and its reliance on newcomers to support demographic stability, labour-market needs and social development. Canadian policy is grounded in the Immigration and Refugee Protection Act (IRPA) of 2002, which established a modern framework balancing three core objectives: economic selection, family reunification, and humanitarian protection. Over the last two decades, Canada has admitted historically high numbers of immigrants and refugees, relying on a points-based system to attract skilled workers, while also expanding pathways for temporary residents, international students, and provincial nominee programs. The article further provides a comparative overview of the EU Member States’ approaches towards the implementation of EU legislation, with particular attention to the Pact on Migration and Asylum (2024). The integration of migrants into host societies remains essential, given the EU’s ageing demographic profile and the growing labour market shortages faced by employers. Over the last fifteen years, the locus of policymaking on asylum seekers and refugees has gradually shifted away from national governments and towards the European Union, as the Common European Asylum System has developed. In Canada, refugee protection remains a central pillar of Canada’s migration model, combining overseas resettlement with inland asylum procedures. Canada is recognized as a global leader in private refugee sponsorship and continues to play a significant role in international resettlement efforts, receiving over 10 percent of global resettled refugees in recent years. Policy adaptations since 2000, including reforms to asylum procedures, enhanced security measures, and cooperation with the United States under the Safe Third Country Agreement, reflect an attempt to balance humanitarian commitments with effective system management.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".