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Record W2906729646 · doi:10.1111/lnc3.12303

New perspectives on the count–mass distinction: Understudied languages and psycholinguistics

2018· article· en· W2906729646 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

VenueLanguage and Linguistics Compass · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFocus (optics)LinguisticsPsycholinguisticsSemantics (computer science)NounComputer scienceField (mathematics)SociologyPsychologyPhilosophyMathematicsCognitionProgramming languagePhysics

Abstract

fetched live from OpenAlex

Abstract Much work has explored the semantics of count and mass nouns from both theoretical and experimental perspectives. In this paper, we explore some of the recent advances in this field, drawing particularly from descriptions of understudied languages and experimental research. We will focus on two dimensions of the count/mass debate. First, we will explore the debate about what can be counted grammatically, that is, how we define atoms and what role extra‐linguistic factors may play in this process. Second, we give an overview of the current debate about counting and measuring, which experimental research suggests are distinct operations, as some scholars in the formal semantics literature have predicted.

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)0.004
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: none
Teacher disagreement score0.878
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.029
GPT teacher head0.285
Teacher spread0.256 · 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