Confronting or incorporating middle-class nation-building? Right-wing responses in the pan-Canadian context
Bibliographic record
Abstract
Canada is often praised for successfully integrating ethnically diverse immigrants into its multicultural nation, so successful indeed that the country has been considered an exception to the twenty-first-century right-wing populist wave. The recent ascent of political mobilization associated with right-wing populist repertoires across Canada, however, has exposed the need to revisit the exceptionalism thesis. With this goal in mind, our article examines the contemporary right-wing responses to the Liberal Party of Canada’s (LPC) post-2015 discourses and policies on immigration and multiculturalism. Building on existing scholarship, we first characterize the LPC’s approach as a nation-building project with strong middle-class partialities that emphasize high skills and human capital. We then explore how right-wing parties oppose or embrace this ‘middle-class nation-building’. Qualitatively analyzing the platforms of center-right parties and those further to the right at the federal and provincial levels (Alberta and Québec), we observe three prevalent response types: those that follow a cultural logic to prioritize identity and values, an economic logic to underline merit and contribution, or a combination of the two. Besides modulating the Canadian exceptionalism thesis, our findings complicate the assumed dichotomy between market-based and cultural forms of nationalism, as political actors can merge them in various permutations.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.018 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".