Discrimination in the Integration of Ukrainian Refugees in Canada
Bibliographic record
Abstract
This thesis investigates discrimination Ukrainian refugees face in Canada through integration experiences into Canadian society to help dismantle anti-immigration and systemic discrimination. The thesis specifically focuses on the discrimination that Ukrainian refugees in Canada encounter with regard to institutional racism and language barriers. In addition, the thesis asserts problemtic impacts of this discrimination on Ukrainina refugees, and efforts that the Ukrainian diaspora in Canada and the Government of Canada are making to alleviate the discrimination and improve the integration of Ukrainian refugees in Canadian society.Ukrainian refugees have been displaced due to Russia's invasion of Ukraine in February 2022, leading to an ongoing geopolitical conflict between the two countries. Focusing on the new wave of Ukrainian refugees who have come to Canada as a result of the 2022 conflict, the thesis utilizes a qualitative research methodology consisting of a content analysis of documents in the form of newspapers. This study is crucial as it fills knowledge gaps in the scholarship regarding refugees in general and Ukrainian refugees in particular, and sheds light on the role of refugee integration in fostering empathetic transformative change and contributing to a thriving society.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.033 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".