Bibliographic record
Abstract
This heroic and indeed Herculean work: Dictionaries and the heroic In the 1550s, the son of the best lexicographer in Europe was writing the introduction to his own first dictionary – a collection, with commentary, of all the Greek words used in the works of Cicero, which would be published under the title of Ciceronianum lexicon graecolatinum . His name was Henri Estienne, and the Latinae linguae thesaurus edited by his father Robert was the definitive dictionary of the Latin language. Robert had for some years been working on an enormous dictionary of classical Greek, and Henri explained that his dictionary of Cicero’s Greek was intended to make a small contribution to this great undertaking, ‘this heroic and indeed Herculean work’. Nearly two centuries later, another dictionary preface was being written. This time, the dictionary was of a whole language rather than one writer’s usage, and of a living language, Irish, rather than a classical one. It was called The English Irish dictionary in English, the language of its definitions, and An focloir bearla Gaoidheilge in Irish. The dictionary would be published in Paris, and would be used by the clergy and clerical students of the Irish College there, and no doubt by those of some or all of the thirty or so other Irish colleges of continental Europe, whose students would return to Ireland to serve a people some of whom spoke no English.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.343 | 0.185 |
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".