Bibliographic record
Abstract
In November 2009, The Dictionary of Old English Project housed at the University of Toronto in Ontario marked a significant milestone, making available a new online version of its highly useful Corpus of Old English produced in and disseminated from Toronto. The DOE Corpus joined the DOE: A to G in being available online from the Robarts Library at the University of Toronto, at home in Canada. Having both the first eight letters of the Dictionary proper, available since 2007, and also now the easily searchable Corpus, which is the database from which the Dictionary entries are developed, means that the Dictionary project has achieved a level of transparency and accessibility still rare in the scholarly world. Since there are but twenty-two letters in the Old English alphabet, the Dictionary has, even by the rawest of reckonings, published about one-third of its entries. In truth, the Project is rapidly closing in on the halfway point, and given the efficiency and foresight of its organizers, work has already been done that will make future entries less onerous. For example, headwords have already been lemmatized (lemmatization is the assignment of spellings to a headword) through to the letter R. Entries have also been drafted for many words occurring later in the alphabet, mostly for compounds formed on words already published or in draft. Entries are far advanced for the massive letter H, the second largest letter in the Old English alphabet (S is the largest), and are equally well in hand for the vexed vowels I/Y and for L. In fact, fully sixty percent of the writing of headwords in the dictionary is complete, a remarkable accomplishment. For confirmed Dictionary-watchers such as I, this means that the prospect is good of having the DOE suddenly arrive at what we would all recognize as the halfway point — the letter M —with a sudden leap and bound through the intervening letters. That will be a truly intoxicating lexicographical moment.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.400 | 0.269 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".