Interpreting the Differences in Signification among Historically-Based Dictionaries of English
Bibliographic record
Abstract
When the history of a particular word is under investigation, the first tool to be consulted is the Oxford English Dictionary (hereafter OED). Spelling variants in historical and typological classification, etymology with the appropriate length of additional explanation, significations according to historical principles with minutely subdivided shades of meaning, dates of the first and the last (in the case of obsolete words) quotations, phrases, and compounds — all this information is given under a headword. The Middle English Dictionary (hereafter MED) has a somewhat different presentation of information; some headwords are n t identical with modern forms, and some of the first quotations under each headword or each signification predate those in the OED. Quotations of Middle English documents are, of course, enriched by way of the variety of manuscript variants of the text quoted. The Dictionary of Old English (hereafter DOE) shows quite a different disciplinary approach. Its uniqueness lies in providing significations which emphasize phrasal expressions and glosses on Latin words. Though a comparison among the three dictionaries is feasible only for headwords from A to G at this stage, it seems worth trying, particularly when another historical tool, the Historical Thesaurus of the Oxford English Dictionary (hereafter HTOED), based on the categories proposed by the Thesaurus of Old English(TOE) and the Historical Thesaurus of English (HTE), has been available since autumn 2009.1 The aim of this paper, then, is to make a comparison among the significations of OED, MED, and DOE, in particular using quotations which exemplify the subdivided senses. On the one hand, we may hope to learn to use these dictionaries properly, with a sufficient knowledge of both their individual merits and peculiarities and their shared proclivities. On the other, it may also be possible to suggest some better ways of structuring the significations, particularly for those headwords which undergo significant change in the transition from Old English to Middle English. The examples for this study are mainly taken from among the words of emotion, which I have been working with for some years, in the DOE fascicles for A to G, in order to keep the comparisons clear. The examples will be presented alphabetically, since that seems the most coherent method of organizing the relevant evidence and assessing the differences among the dictionaries for the significations of the relevant headwords. If the ideal is to gain a sense of the whole history of a given word by “simply pushing a button of your PC,” then the three diachronically based dictionaries need to work from a common basis of understanding, especially with respect to signification.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".