Comparing language and religion in normative arguments about linguistic justice
Bibliographic record
Abstract
Abstract Many of the most influential theorists of linguistic justice make arguments on the basis of comparisons between language and religion. They claim either that (1) language, by contrast with religion, cannot be separated from the state or that (2) unequal official linguistic recognition, just like unequal official religious recognition, is morally problematic. This article argues that careful attention to debates about liberalism and the place of religion in public life invites us to question the two above‐mentioned liberal assumptions about religion underlying many arguments concerning linguistic justice based on (dis)analogies between language and religion. The hope is that such critical scrutiny is likely to shed some light on normative questions of linguistic justice, more precisely on questions about the legitimacy of granting more recognition to certain languages, usually those of national native groups (as opposed to groups resulting from more or less recent immigration).
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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 | 0.028 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.067 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.011 | 0.009 |
| 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".