Bibliographic record
Abstract
In this chapter it will be argued that a proper understanding of grammaticalization has to take into account the driving force of lexically underspecified constructions. Using evidence from an extensive qualitative and quantitative corpus study in the York-Toronto-Helsinki Parsed Corpus of Old English Prose (YCOE), it will be suggested that the OE demonstrative se developed into the definite article due to the emergence of an abstract, syntactic, and lexically underspecified macro-construction with a determination slot for marking definiteness in early Old English. This slot becomes a functionally exploitable structural category itself, which leads to the recruitment of the demonstrative as a default slot filler (= definite article). What has traditionally been interpreted as a case of grammaticalization on the morphosyntactic level (OE demonstrative se > ModE article the ) is at the same time a case of “grammatical constructionalization.” The demonstrative does not grammaticalize on its own but in the context of an emerging schematic construction, which is formalized as the [[Xdeterminative]DETERMINATION + [Zcn]HEAD]NP{def}– construction. The emergence of this construction is best explained by a usage-based, form-driven, analogical model of morphosyntactic change which takes into account the frequency of linguistic surface forms (i.e. concrete tokens) and the formal influence of taxonomically related constructions.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".