The New Economy and New Technologies in Montreal: Between Linguistic Protectionism and Liberalism
Bibliographic record
Abstract
The new economy and new technologies in montreal : between linguistic protectionism and liberalism Based on ethnographic research, this chapter examines the language practices and discourse on language within a Montreal company expanding into new markets. Data reveals a work environment which is French, but in which a technolect has developed drawing heavily on terms used in English postproduction software. Strategies for the management of bilingual and multilingual communication needs create a buffer zone, nevertheless when looked at more closely, it becomes clear that bilingualism is present in many work interactions throughout the structure of the company. Strong contradictions in respect to bilingualism can be found in the discourse on language, with bilingualism described at times as a resource and necessary to being a competitive player in Quebec, both at the individual and the collective level. Bilingualism, however, is also perceived as a threat to the vitality of French.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".