MétaCan
Menu
Back to cohort
Record W4402124072 · doi:10.1007/978-3-031-64167-1

The North Germanic Morphosyntax of Modern English

2024· book· en· W4402124072 on OpenAlexfundno aff
Joseph Emonds, Jan Terje Faarlund

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
FundersNorges ForskningsrådUniversity of GlasgowGeorg-August-Universität GöttingenUniversidad de SevillaUniversity of AberdeenYork University
KeywordsGermanic languagesLinguisticsHistoryPhilosophyGerman

Abstract

fetched live from OpenAlex

This book makes fascinating reading.First, there are all the arguments that a host of linguistic properties in Middle English, many of which survive in Modern English, originate in Norse, the language spoken by the Scandinavian immigrants who settled in England in the ninth to eleventh centuries.As a result of the migration a new form of Germanic developed, with a syntax which is more Norse (Old Scandinavian) than Old English and a vocabulary which is more Old English than Norse, even though it also contains a good deal of Norse words.This form of English developed first in the Danelaw region, in the East and North-East of England, but later became the dominant form in all of Britain.On a general enough level, this is the picture presented by much research on the history of English, but Joseph Emonds and Jan Terje Faarlund, the authors of this book, have found an even greater preponderance of Norse-based grammatical features over Old English-based features than recognized by other researchers, and argue on that basis that Middle English grammar is North Germanic, not West Germanic.They call this the Anglo-Norse Hypothesis.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.186
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.194
Teacher spread0.177 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicLinguistics, Language Diversity, and IdentityFrench-language works237,207