How does interculturalism facilitate diversity incorporation into the cultural policy mainstream? Montreal’s case study
Bibliographic record
Abstract
Abstract After conceptualizing multiculturalism and interculturalism as two main categories of analysis, I propose an interpretive framework to identify the main drivers of change/continuity in mainstream cultural policy when incorporating diversity. I will use Montreal as a case study and I will undertake documentary analysis and in-depth interviews with the main key-agents of cultural governance. The findings confirm one main pattern: interculturalism is a policy approach that facilitates the process of diversity incorporation in mainstream cultural policy, while multiculturalism is the basis of most of the tensions identified. In fact, to understand the initial tensions that decide continuity/change in cultural policies, two notions of culture are at odds: a narrow view which perceives immigrants as national bearers (ethnic-based view of culture) and a broader notion viewing culture as creative expression (an artistic-based view). The article will culminate with a proposal for a discussion framework to enable further research linking interculturalism/cultural policy.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".