Perceptual functionality of morphological redundancy in Choguita Rarámuri (Tarahumara)
Bibliographic record
Abstract
A recent cross-linguistic survey suggests redundant marking of the same meaning by multiple morphological markers to be more widely attested than commonly believed. While this phenomenon (referred to as multiple (or extended) exponence in the morphological literature) has been examined within the context of morphological theory and diachronic research, little work has investigated the processing of morphological redundancy and synchronic motivations for its use. This paper reports a field speech-in-noise experiment to assess perceptual functionality of redundant markers in an agglutinating, morphologically complex language of Northern Mexico, Choguita Rarámuri (Tarahumara). This language possesses morphological patterns in which a meaning is redundantly cued by two consecutive suffixes, and where the second (outer) suffix is optional. We show that the effect of adding the optional suffix varies with the overall likelihood of recognising its meaning in context: cue redundancy helps when recognition of the cued meaning is difficult but hurts when recognition of the cued meaning is easy. The results are interpreted as support for the operation of Grice's Maxim of Clarity in spoken word recognition and/or production: the listener expects the speaker to say only as much as is necessary to transmit the message.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".