Articulating minority nationhood: cultural and political dimensions in <scp>Q</scp>uébec's reasonable accommodation debate
Bibliographic record
Abstract
Abstract Given their precarious position within larger states, national minorities cannot rely on federal governments to affirm their nationhood. Moreover, insofar as nationhood is predicated on a shared history, language and culture, immigrants place additional strains on the maintenance of national distinctiveness and the political claims that derive from it. In 2006–2007, following a series of confrontations over religious practices in the public sphere, Québec's provincial government appointed the Bouchard–Taylor Commission to investigate avenues for the accommodation of immigrant‐related cultural and religious differences. While it failed to generate policy, the commission did provide a discursive space for the (re)assertion of Québécois nationhood. Analysing the production of national identity in newspaper debates of the Bouchard–Taylor report, we offer an alternative to the ethnic–civic paradigm in nationalism theory. Rather than treat ethnic and civic as two separate ends of a single continuum, we conceptualise a relationship between two dimensions: one of culture and one of politics. We show that in contemporary articulations of Québec national identity, the prerequisites of political membership derive their meaning from a productive tension between blood‐based and adoptive conceptions of national culture.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.020 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".