State Traditions and Language Regimes: A Historical Institutionalism Approach to Language Policy
Bibliographic record
Abstract
Abstract This paper is an elaboration of a theoretical framework we developed in the introductory chapter of our co-edited volume, State Traditions and Language Regimes (McGill-Queen’s University Press, 2015). Using a historical institutionalism approach derived from political science, we argue that language policies need to be understood in terms of their historical and institutional context. The concept of ‘state tradition’ focuses our attention on the relative autonomy of the state in terms of its normative and institutional traditions that lead to particular path dependencies of language policy choices, subject to change at critical junctures. ‘Language regime’ is the conceptual link between state traditions and language policy choices: it allows us to analytically conceptualize how and why these choices are made and how and why they change. We suggest that our framework offers a more robust analysis of language politics than other approaches found in sociolinguistics and normative theory. It also challenges political science to become more engaged with scholarly debate on language policy and linguistic diversity.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".