MétaCan
Menu
Back to cohort
Record W3011066306 · doi:10.1075/alal.00001.abb

Aspects of word formation processes in Luro

2020· article· en· W3011066306 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

VenueAsian Languages and Linguistics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSwearing, Euphemism, Multilingualism
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsWord formationLinguisticsNounMorphology (biology)PronounVerbComputer scienceHistoryBiologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Luro, an Austroasiatic language of the Mon-Khmer group is spoken in the Teressa island of the Andaman and Nicobar group of islands in the Bay of Bengal, India. Luro is a critically endangered language spoken by less than 2,000 speakers ( Directorate of Census Operations 2011 ). The morphology of Luro is virtually undescribed in detail so far. The previous works are restricted to deRoepstorff (1875) , Cruz (2005) , Man (1889) and Rajasingh (2019) which are limited to wordlists and a partial dictionary. This is the first-ever account of word formation process in the language. Word formation processes include among others, compounding and derivation across grammatical categories. Incorporation is used in verb morphology. Although language does not have an extensive case marking system postpositions appear on some nouns optionally. Nouns are marked for duality and plurality but not for gender. Negation is indexed with pronoun morphology and participates in formation of antonyms. Kinship terminology and Number System have also been dealt with to represent diverse word formation processes. 1

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.511
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.009
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 integrity0.0000.000
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 head0.334
Teacher spread0.311 · 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