MétaCan
Menu
Back to cohort
Record W3173750434 · doi:10.1086/714247

How To Distribute Events: <scp>ʔ</scp>ay<scp>ʔ</scp>aǰuθəm Pluractionals

2021· article· en· W3173750434 on OpenAlexaff
Marianne Huijsmans, Gloria Mellesmoen

Bibliographic record

VenueInternational Journal of American Linguistics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPluralAffixReduplicationPredicate (mathematical logic)LinguisticsComputer sciencePhilosophyProgramming language

Abstract

fetched live from OpenAlex

In this paper, we discuss two types of plural marking, C1C2 reduplication and a -Vg- affix, on verbs in ʔayʔaǰuθəm (Comox-Sliammon), a Central Salish language. We argue that C1C2 plural reduplication on verbs indicates pluractionality, creating a predicate that encodes a plurality of spatiotemporally distributed events. We further argue that the distribution of events must be in both time and space. This has implications for the typology of pluractionals, since the distribution requirement for events is more restrictive than what has been reported for other languages. In contrast, the -Vg- affix marks plural participants and does not require plural 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.

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)0.081
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.081
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.277
Teacher spread0.254 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of American LinguisticsSame topicSyntax, Semantics, Linguistic VariationFrench-language works237,207