Bibliographic record
Abstract
Linguistic Rivalries weaves together anthropological accounts of diaspora, nation, and empire to explore and analyze the multifaceted processes of globalization characterizing the migration and social integration experiences of Tamil-speaking immigrants and refugees from India and Sri Lanka to Montréal, Québec in the late twentieth and early twenty-first centuries. In Montréal, a city with more trilingual speakers than in any other North American city, Tamil migrants draw on their multilingual repertoires to navigate longstanding linguistic rivalries by arguing that Indians speak “Spoken Tamil” and Sri Lankans speak “Written Tamil” as their respective heritage languages. Drawing on ethnographic, archival, and linguistic methods to compare and contrast the communicative practices and language ideologies of Tamil heritage language learning in Hindu temples, Catholic churches, public schools, and community centers, this book demonstrates how processes of sociolinguistic differentiation there are mediated by ethnonational, religious, class, racial, and caste hierarchies. Indian Tamils showcase their use of the “cosmopolitan” sounds and scripts of colloquial varieties of Tamil to enhance their geographic and social mobilities, whereas Sri Lankan Tamils, dispossessed of their homes by civil war and restricted in travel, instead emphasize the “primordialist” sounds and scripts of a pure “literary” Tamil to rebuild a homeland and launch a “global” critique of racism and environmental destruction. This book uses the ethnographic and archival study of Tamil mobility and immobility to expose the mutual constitution of elite and non-elite global modernities, defined here as language ideological projects in which migrants objectify dimensions of time and space through scalar metaphors.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".