‘<i>Ch'us mon propre Bescherelle</i>’: Challenges from the Hip‐Hop nation to the Quebec nation<sup>1</sup>
Bibliographic record
Abstract
We examine the uses of and attitudes towards language of members of the Montreal Hip‐Hop community in relation to Quebec language‐in‐education policies. These policies, implemented in the 1970s, have ensured that French has become the common public language of an ethnically diverse young adult population in Montreal. We argue, using Blommaert's (2005) model of orders of indexicality, that the dominant language hierarchy orders established by government policy have been both flattened and reordered by members of the Montreal Hip‐Hop community, whose multilingual lyrics insist: (1) that while French is thelingua franca, it is a much more inclusive category which includes ‘Bad French,’ regional and class dialects, and European French; and (2) that all languages spoken by community members are valuable as linguistic resources for creativity and communication with multiple audiences. We draw from a database which includes interviews with and lyrics from rappers of Haitian, Latin‐American, African‐American andQuébécoisorigin.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".