Switch-reference and its role in referential choice in Mbyá Guaraní narratives
Bibliographic record
Abstract
Abstract Switch-reference has been analyzed as a reference tracking mechanism, whose main function is to avoid ambiguity of reference. One domain where this function has been argued to manifest itself is referential choice. Kibrik (Kibrik, Andrej. 2011. Reference in discourse. Oxford: Oxford University Press) notably proposed that switch-reference marking plays the role of a referential aid, which helps to prevent referential conflict, thereby enabling the production of reduced referential expressions such as pronouns and zeros. The present study probes this theory through an analysis of the role of switch-reference marking in multifactorial models of referential choice in Mbyá Guaraní. We show that while switch-reference increases the likelihood of mention reduction in Mbyá Guaraní, this effect is marginal relative to other predictors of referential choice. We argue that this result is compatible with the analysis of switch-reference as a referential aid, but also supports analyses that emphasize the multiplicity of its functions, beyond the disambiguation of reference.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".