Linguistic minorities and the multilingual turn: constructing language ownership through affect in cultural production
Bibliographic record
Abstract
Abstract The “multilingual turn” brings questions of language ownership to the forefront of debates about linguistic minority governance. Acadian minority cultural producers construct language ownership using multiple languages and targeting multilingual publics, but use ideologies of monolingualism to situate Acadian authenticity in place and time. As globalization brings minority language governmentality onto global terrains, cultural workers manage the tension between multilingualism and ownership through affective registers. This paper contributes to theorizing language and governmentality by understanding affect as a discursively produced register that serves to legitimate the distribution of resources. I follow the role affect plays in constructing linguistic minority subjects as agents of globalization. I flip cultural entrepreneur’s understanding of themselves as liberal agents of linguistic change and show how they are constrained by the political salience of monolingualism. I draw on ethnographic fieldwork carried out in the field of linguistic minority cultural production in Acadie to track moments when questions of ownership appeared. I pay attention to the role affect played in navigating the tensions between the economic value of multilingualism for global markets and the remaining political salience of monolingualism for minorities. Affect served to reproduce the minority speaker as a particular type of subject, one “attached” to a community constructed as ideally monolingual, either in the past, present or future. I then map out global linguistic minority governmentality to show how knowledge production on language is embedded in the tensions experienced by linguistic minority cultural producers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".