Pronoun interpretation in Italian: Exploring the effects of prosody
Bibliographic record
Abstract
We explore potential effects of prosody on pronoun interpretation in Italian, building on previous research which has shown that second language learners/users (L2ers) assign non-target interpretations to overt pronouns. We investigate effects of contrastive stress and pause, proposing that these will result in changes to default antecedent preferences for overt and null pronouns, for L2ers and for native speakers. An experiment was conducted, involving English-speaking L2ers of Italian and Italian native speakers. Participants were presented with auditory stimuli like Lorenzo ha scritto a Roberto quando Ø/lui si è trasferito a Torino ‘Lorenzo wrote to Roberto when (he) moved to Turin’ and indicated their preferred antecedent for the pronoun. Overt versus null pronouns, presence versus absence of stress on overt pronouns, and presence versus absence of pause between clauses were manipulated. The results yielded significant differences for antecedent choices between null and overt pronouns, consistent with earlier literature. In addition, stress was significant for both groups. Implications of a prosodic approach to ambiguity resolution are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".