ASYLUM SEEKER INTEGRATION POLICIES IN GERMANY AND CANADA
Bibliographic record
Abstract
This thesis contributes to the emerging literature on asylum seeker integration by carrying out a critical discursive policy analysis of the integration frameworks in Germany and Canada. By the application of What is the Problem Represented to Be? by Bacchi. The thesis examines the construction of the difficulties of accessing employment, healthcare, and social inclusion by asylum seekers through an analysis of policy documents and official narratives. It concludes that even though both nations present their policies as helpful and ready to comply with international commitments, they carry opposing assumptions and influence asylum seekers as weak people in need of protection and a potential drain on national resources. BAMF Brief Analysis demonstrates how German integration discourse frames parent-child multilingualism in migrant Muslim families as individual failure, diverting attention from structural gaps in education and support. Through a securitization lens, such framings construct language diversity as a threat, justifying assimilationist policies. Constructivist IR theory emphasizes that policy narratives actively produce social realities by defining belonging, privileging an exclusionary notion of ‘Germaneness. Applying Bache’s WPR approach reveals how problem representations legitimize deficit models of multilingualism, reinforcing Eurocentric norms and marginalizing hybrid identities. This comparative design will allow us to analyze how liberal democracies manage to reconcile humanitarian commitments with national security concerns. The thesis made is that these representations are not neutral but indicate wider conflicts between humanitarian principles and security-based governance, and in the end, restrain the transformative capacity of integration policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".