On Multi-Using Materials from The Dictionary of Old English Project, with Particular Reference to the hapax legomena in the Old English Translation of Felix’s <i>Vita Guthlaci</i>
Bibliographic record
Abstract
Like all responsible Anglo-Saxonists, I use Toronto Dictionary of Old English (DOE) materials heavily. Indeed, as long ago as 1989 Ashley Amos and Toni Healey sent me a CD-ROM version of their files, some years ahead of the first public release of the Dictionary of Old English Corpus in Electronic Form database, which we now take so much for granted; thus, I have benefited from access to their electronic files for along time now. The arrival of the CD led to a decision that delayed publication of the Thesaurus of Old English, a pilot-study for the Historical Thesaurus of the Oxford English Dictionary. With the possibility of running checks on the words and meanings taken from standard dictionaries of Old English, it also became possible to supply the thesaurus entries with a minimal flagging system: superscript o for hapax legomena, p for words found only in poetry, g for glosses, and q for dubious words. Checking for even these four flags was a time-consuming and problematic process, as we indicated in the Introduction to the TOE. We toyed with adding various indications to this small group of flags to mark, for example, single forms found in multiple manuscripts, relative trustworthiness among types of glosses, or everyday elements within poetic compounds. Most compelling of all arguments against a more elaborated system of flagging was the state of the available dictionary resources. Except for the letters of the alphabet already edited by the DOE team, D (1986) and C (1988), the dictionaries were insufficient even for this level of detail, but with the help of the editorial materials of The Dictionary of Old English Project it was feasible to test for and apply the minimal flagging I proposed. Before the arrival of the CD-ROM files, use of the two sets of DOE microfiches (1980, 1985) was a cumbersome process suited only to the investigation of small amounts of data.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.141 | 0.063 |
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".