Some Facts About Quantification and Negation One Simply Cannot Deny: A Reply to Gennari and MacDonald
Bibliographic record
Abstract
Research on language acquisition has recently focused on the interaction between quantifiers and negation. One generalization presented in the literature is the so called Observation of Isomorphism, the observation that children's semantic scope coincides with syntactic scope (see Musolino (1998)). The most recent con tribution to the debate on scope resolution is due to Gennari and MacDonald (2005/2006) (G&M henceforth). Their proposal attempts to derive the Observa tion of Isomorphism from the distributional properties of the input to which chil dren are exposed. The article presented here evaluates the proposal by G&M. First, we review the existing findings on children's interpretation of negative quantified sentences. The findings show that the generalization presented by Musolino (1998) is incor rect, thereby calling into question any attempt to derive that generalization. Sec ond, we highlight children's ability to go beyond the input, an issue that must be addressed by G&M if they want to derive any generalization about child language from the properties of the input.
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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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.006 | 0.030 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.034 | 0.059 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".