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Record W2579891069

Past tense formation with irregular lexical verbs in Canadian English

2013· article· en· W2579891069 on OpenAlexaboutno aff
Tara Glickman

Bibliographic record

VenueQSpace (Queen's University Library) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsPast tenseAmerican EnglishCasualPresent tenseVariation (astronomy)PsychologyHistoryNorth American EnglishSet (abstract data type)Modal verbBritish EnglishCategorical variableVerbComputer science
DOInot available

Abstract

fetched live from OpenAlex

There is a set of lexical verbs in English ending in /-l, -m, -n/ (e.g., to spill, to dream, to burn) that receives a different form of the past tense in British versus American English. While in American English these verbs typically receive the regular past tense form /-d/ (e.g., spilled), in British English the irregular devoiced form /-t/ (e.g., spilt) (occasionally accompanied by ablaut) is more common. The form of the past tense in these verbs in Canadian English is, however, less categorical. The main objective of this study is to examine variation in the usage of the past tense in this set of lexical verbs in contemporary Canadian English. The investigation consists of three components: (a) informal interviews of Canadian and American university students to examine their usage of the past tense for these verbs in casual speech, (b) a formal survey to assess how Canadians perceive the usage of the variable past tense forms and (c) a corpus-based comparison of both past tense forms using Canadian and American corpora. The findings suggest that the majority of Canadian English speakers have mixed usage of /-t/ and /-d/ past tense forms.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.184
Teacher spread0.178 · 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
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

Citations0
Published2013
Admission routes1
Has abstractyes

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