Public discourse on refugees in France and Canada: a comparative analysis
Bibliographic record
Abstract
This research is meant to provide insight into the public discourse surrounding Muslim refugees in the countries where they have been resettled. In general media, the plight of refugees is often discussed; however, very few studies have been conducted which examine the relationship between refugees and public discourse, which leads to the necessity of this study. This study follows the plight of refugees in France and Canada because of the vastly different public discourse surrounding refugees in both countries. For the purposes of this research, two sources of public discourse from each country were selected for analysis. One source from each country is representative of the political-left, and the other, the political-right. The analysis is supplemented by an interview with a Canadian Imam who provides additional insight into the life of the average refugee in Canada. The findings from this study show that social, interpersonal, and communication issues are more highly publicized in French than Canadian public discourse. The public discourse representative of the French political-right draws attention to issues surrounding refugees in France, likely with the intent to tarnish the reputation of the refugees themselves. However, the public discourse representative of the French political-left showed deep sympathy for the refugees in France. Canadian public discourse primarily focused on the political effects of refugees landing in Canada, but social, interpersonal, and communication issues were largely unreported by both sides of the public-discourse. The political-left and political-right in Canada shared sympathy for Syrian refugees where French public discourse provided sympathy on the left and criticism on the right. This is problematic because important issues concerning the well-being of refugees are largely ignored by the Canadian sources of public discourse. The lack of depth within Canada’s public discourse surrounding refugees shows that there is a general lack of understanding of the plight of refugees even after they settle in Canada.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.033 | 0.010 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".