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REDUPLICATION INITIATED THROUGH DISCOURSE MARKERS: A CASE OF HADOTI.

2020· article· en· W3042829546 on OpenAlex
Gulab Chand, Somdev Kar

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

VenueDialectologia · 2020
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsNetwork for Business Sustainability
Fundersnot available
KeywordsReduplicationPhenomenonVerbLinguisticsFocus (optics)Variety (cybernetics)SentenceHindiIndonesianDiscourse markerFeature (linguistics)HistoryComputer scienceSociologyPhilosophyArtificial intelligenceEpistemologyPhysics

Abstract

fetched live from OpenAlex

Reduplication is a common morphological process in many languages, particularly in South Asia. This study focuses on the reduplication phenomenon in Hadoti, where it ensues with the help of a discourse marker /rə/, functioning as an emphasizing agent in the process. This marker comes between the base and the reduplicant for expressing emphasis in work or action or verb (as in /kʰa rə kʰa/ ‘do eat,’ etc.). In Hadoti, /rə/ functions as a vocative case marker when it comes at the end of the sentence as in /ram ɡjo rə/ ‘Ram went’. However, when /rə/ occurs in between the base and the reduplicant, the stress shifts on the latter from the base. Phenomena of reduplication with a specific focus on the use of /rə/ are discussed in the current study using the constraints like *CLASH, and STRESS-TO-RED, etc. This particular phenomenon is predominantly present in the case of verbs in Hadoti, which is a unique feature of this variety of Hindi.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score1.000

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 communication0.0000.000
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 head0.158
GPT teacher head0.432
Teacher spread0.274 · 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