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
In retrospect the foundation of the Dictionary of Old English reads like the New World coming to the aid of the Old. Its founder, Angus Cameron, had the vision and the hope needed. His dissertation on a difficult Old English word had shown to him the insufficiency of Old English lexicography, no better really in the late 1960s than it had been a hundred years before. Neil Ker’s Catalogue of Manuscripts Containing Anglo-Saxon had been published in 1957, and Angus for his thesis had rearranged its contents by turning it into a classified catalogue of texts for him to use as he hunted through the texts for his word in its many divergent senses. The standard dictionary at that time was effectively a work of the 1830s and earlier, supplemented by a good Mancunian scholar at the turn of the century. The work was mainly at second hand, relying on two good German lexicographers and on glossaries and translations of Anglo-Saxonists some good, others less so. Angus’s vision was that the basis was the textual evidence of the manuscripts and that a new age of technology had dawned, available in Canada, rich then, and led and encouraged by John Leyerle, of the States (resident as a professor in Toronto), a conference was organized to give substance to a hope. The assembled Anglo-Saxonists were united in spirit — rye, in my recollection — and it was determined that Toronto, with space provided in the Robarts Library by the University of Toronto, would be an excellent place for a new dictionary based on new technology, photocopies of manuscripts, so that all texts could be checked rather than merely used at second hand, and on the new electronic invention, the computer, at that early stage of its rapid development, especially good for concordances. A Canadian, Elaine Quanz, who had worked with Angus, was given the task of typing out all the texts of Old English, several thousands of them, for concording by the computer. If you wish to build high you need a firm foundation, and Angus saw to it that the foundation of the new dictionary was firm.
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.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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