Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Praised by Franz J. Hausmann as the best description of the English language at the end of the 17th century, Abel Boyer's <it>Royal Dictionary. In Two Parts. First, French and English. Secondly, English and French</it> (<cross-ref type="bib" refid="bib2">1699</cross-ref>) is one the most important dictionaries of all time. It was published 11 years after Guy Miège's <it>Great French Dictionary. In Two Parts. The First, French and English; The Second, English and French</it> (<cross-ref type="bib" refid="bib7">1688</cross-ref>), and both works dominated bilingual English-French lexicography in the 17th and 18th centuries. Influential as they were, however, these works remain largely unexplored. Two previous articles (Cormier <cross-ref type="bib" refid="bib19">2003</cross-ref> and <cross-ref type="bib" refid="bib20">2005</cross-ref>) examined the influence of the <it>Dictionnaire de l’Académie Françoise</it> on the French-English part of Abel Boyer's <it>Royal Dictionary</it>. The current study investigates whether or not the English-French part of Boyer's dictionary was inspired by the <it>Great French Dictionary</it> by Guy Miège. This is a relevant subject given the accusations of plagiarism against Boyer found in an anonymous text attributed to Miège and the fact that, in the front matter of the <it>Royal Dictionary</it>, Boyer made no explicit mention of Miège as a source for the English-French part: he instead rather harshly criticized Miège. Did Boyer really base the English-French part of his work on Miège's <it>Great French Dictionary</it> of 1688&quest; If this question can be answered affirmatively, what is the extent of that influence&quest; Did Boyer depend upon Miège for the nomenclature, the microstructure, or both&quest; These are the questions this article will endeavour to answer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it