Investigating the emergence of the definite article in Old English: About categorization, gradualness and constructions
Bibliographic record
Abstract
The article attempts to shed new light on the question if a definite article existed in Old English. First, it tries to determine what it actually means to be an article, discusses several criteria of ‘articlehood’ that have been proposed in the literature, and demonstrates that only some of them are useful for identifying the category in Old English. Next, a distinction between ‘primary’ and ‘secondary’ characteristics of articles is proposed, and the primary ones are employed in a corpus study of occurrences of the OE form se in various prose texts from the York-Toronto-Helsinki Parsed Corpus of Old English Prose (YCOE). The results of that study highlight the necessity to reconceptualize the emergence of the article within a construction-grammar model, and to take notions like gradience and gradualness into account. It will be argued that the emergence of the definite article in English reflects the prior establishment of a determination slot in the prehead of the NP. Being lexically underspecified, such a grammatically established slot has the potential of recruiting default fillers, and in the case of OE definite NPs that filler happened to be se . Evidence will be provided to show that a determination slot had indeed already emerged in Old English. It was a characteristic feature of most definite NP constructions and triggered the gradual grammaticalization of the demonstrative se .
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".