REDUPLICATION INITIATED THROUGH DISCOURSE MARKERS: A CASE OF HADOTI.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".