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Verb-Object Order in Early Middle English

2001· book-chapter· en· W129133793 on OpenAlexaboutno aff
Anthony Kroch, Ann Taylor

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle EnglishWord orderOld EnglishSyntaxOrder (exchange)VerbObject (grammar)HistoryLinguisticsQuarter (Canadian coin)LiteratureArtPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Abstract In the standard account (Canale 1978, van Kemenade 1987, Lightfoot 1991), there is a sharp divide in word order between Old and Middle English. Old English is INFL-final and OV while Middle English is INFL-medial and VO. Indeed, Lightfoot gives an account of the transition from Old to Middle English based on a catastrophic reanalysis in the twelfth century (Lightfoot 1991, 1999) and, viewed from a certain distance, this story has considerable plausibility. Thus, up until the entry for II22 CE, the syntax of the Peterborough version of the Anglo-Saxon Chronicle, the manuscript which extends furthest into the twelfth century, is that of standard literary Old English. The brief continuations, which end in II54, are hard to interpret but are not revolutionary in their syntax. These are the last documents of Old English. Then in the first quarter of the next century, several prose texts of West Midlands provenance appear, the Ancrene Riwle and the Katherine Group of saints’ lives, whose word order is considerably more modem. INFL-final word order seems absent and surface OV word order be comes a minority pattern. Nevertheless, there is reason to doubt the standard account.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.029
GPT teacher head0.204
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2001
Admission routes1
Has abstractyes

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