Aren’t Prosody and Syntax Marking Bias in Questions?
Bibliographic record
Abstract
As first observed by Ladd in 1981, English polar questions with high negation (e.g., Aren’t they adding a menu item?) can be used both to check the speaker’s belief that the proposition p is true (e.g., p = they are adding a menu item) and to check the addressee’s belief that p is not true (¬ p). We hypothesized that this ambiguity can be disambiguated prosodically. We further hypothesized that the prosodic disambiguation is absent in German, because the checked proposition can be marked morpho-syntactically, with questions with high negation checking p and low negation questions (e.g., Are they not adding a menu item?) checking ¬ p. A production study tested these hypotheses with 24 speakers of Western Canadian English and German each (764 and 767 total utterances, respectively). The results showed that, when the speaker originally believed p and the addressee implied ¬ p, English speakers preferred questions with high negation over low negation questions, confirming Ladd’s observation, and used intonation to mark whose proposition they were checking, as hypothesized. By contrast, German speakers marked this distinction morpho-syntactically, realizing mostly questions with high negation to check their own proposition and low negation questions to check the addressee’s proposition. Their prosody, in turn, was largely determined by the morpho-syntactic question form. The study further manipulated the speaker’s certainty of the checked proposition, but, in contrast to studies on Romance languages, found that certainty itself was not marked.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".