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Record W7125964169 · doi:10.18148/lfg/2025.v30i.72

Categories don’t take precedence

2025· article· en· W7125964169 on OpenAlexaff
Frances Dowle, Ash Asudeh

Bibliographic record

VenueOpen MIND · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsCarleton University
Fundersnot available
KeywordsWelshImperfectComponent (thermodynamics)GrammarWord (group theory)Relation (database)

Abstract

fetched live from OpenAlex

The morphological component of an LRFG grammar is responsible for selecting the word forms (Vocabulary Items, or VIs) which express a given sentence. VIs may realize only a subset of the information in a sentence, but MostInformative_f (MIf ) and MostInformative_c (MIc ), which evaluate the f- and c-structure information a VI realizes (respectively), ensure that sentences are expressed using the fewest VIs that realize the most information possible. Welsh has positive, negative and neutral forms of the copula in the present and imperfect paradigms which compete to realize copula-containing structures. The Welsh data regarding which form is selected in different contexts is used to show two important conclusions: (1) that constraining equations have a different status to defining equations in VIs, the former not contributing to the evaluation of MIf , and (2) that MIf outranks MIc when the two metrics return different VIs according to their evaluation.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.989

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.048
GPT teacher head0.294
Teacher spread0.246 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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