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Record W2506821074 · doi:10.1075/la.210.07arm

Derivation by gender in Lithuanian

2014· book-chapter· en· W2506821074 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

VenueLinguistik aktuell · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLithuanianNumeral systemNounLinguisticsGrammatical genderPerspective (graphical)Feature (linguistics)UtterancePart of speechExpression (computer science)Computer sciencePsychologyArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

For a long time, grammatical gender has been viewed solely as a feature inherent to nouns and necessary to track agreement between noun and other elements within an utterance (Aikhenvald 2003; Hockett 1958; Corbett 1991). However, since the seminal article of Ritter (1991), other uses and characteristics of gender as an abstract feature have been brought to light. For example, gender has been argued to play a role in numeral classification (Mathieu 2012), or serve as an expression of speaker perspective (Armoskaite & Wiltschko 2012; Gerdts 2011). This study focuses on the role of gender in the derivation of nouns. Based on Lithuanian (Baltic), the paper argues that gender may derive nouns from nouns, adjectives and verbs.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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