On ƒent bien que c’eƒt-là du plus Haut-Allemand » : les dénominations de langues comme formules évaluatives dans le genre des remarques
Bibliographic record
Abstract
In this paper, we analyze the function of language denominations in the normative discourse of 17th-century remarques, as well as in Éléazar de Mauvillon’s Remarques sur les germanismes (1753 [1747], 1754). Stemming from the initial observation that certain denominations may appear descriptive, but in reality, fulfil a normative function, this analysis identifies the evaluative dynamics associated with different languages. The results reveal that language denominations are generally used in a normative manner, and yet, the degree of prescriptiveness varies in relation to the linguistic group and its status. A significant divergence is found in the use of Germanic language denominations. While they are used descriptively in 17th-century remarques, Mauvillon employs them in a strongly prescriptive manner. These conclusions reflect the impact of linguistic ideology on the conception of normative discourse across different works.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".