Bibliographic record
Abstract
Born in New Zealand, Brian Merrilees completed his B.A. (1960) and M.A. (1961) at the University of Otago. Like many other aspiring scholars of French, he then went to the Sorbonne, graduating as Docteur de l’Université de Paris in 1964. His thesis, an edition of Le petit Plet, later published as volume 20 (1970) by the Anglo-Norman Text Society, launched his academic career as a scholar of Anglo-Norman, editor of texts and philologist par excellence. In all, he has edited or co-edited six editions of Anglo-Norman texts. All bear the hallmark of his meticulous scholarship, based on a sound knowledge of the grammar and philology of Old French and of the specificity of Anglo-Norman. In recent years, his research has taken a different course as he has pursued his interest in lexicography. Out of this interest has come a substantial body of work on medieval glossaries, lexicons, and dictionaries, including three collaborative editions of Latin-French dictionaries and many articles and conference papers. Lexicography is the current focus of his work, with editions of two further dictionaries underway.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.325 | 0.201 |
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".