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Record W3036400034 · doi:10.1515/jall-2019-0009

Dàgáárè complex constructions: Serial verb constructions, multi-aspectual constructions and coordination

2019· article· en· W3036400034 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of African Languages and Linguistics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVerbLinguisticsCovertComputer scienceVariety (cybernetics)Sequence (biology)Semantic propertyArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Abstract The Serial Verb Construction (SVC) phenomenon is widely researched across many languages. It is generally regarded as a construction in which two or more verbs share the same arguments within a single clause. The verbs in the series must share some grammatical properties such as tense, aspect and polarity. However, there is a verb sequence construction in Dàgáárè that shows apparent similarities to SVCs but with different values for aspect on the verbs. This paper investigates the internal structure of Dàgáárè SVCs and other verb sequence constructions such as multi-aspectual constructions (MACs) and coordinate structures. Applying a variety of syntactic and semantic tests, the paper distinguishes SVCs from MACs and coordination and shows the relation between MACs and coordination. Based on the results of the tests, I argue that although MACs have some properties of SVCs, they are not SVCs. Rather; I conclude that MACs pattern with coordination or covert coordination in Dàgáárè and they are perceived to express distinct events.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.263
Teacher spread0.242 · 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