Negative scope, temporality, fixedness, and right- and left-branching
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract ‘Negative scope’ concerns what it is that is negated in an utterance with a negative morpheme. With English and Japanese conversational data, we show that for an English speaker, calculating negative scope requires that recipients incrementally keep track of all the material in the clause that follows the negative morpheme, which comes early in the clause. In contrast, the negative morpheme comes late in the clause in Japanese; thus it would seem that recipients need to hold in memory all the material in the clause preceding the negative until the negative morpheme is produced. Several features of Japanese grammar, however, suggest that this characterization is not accurate. We argue that prosody, grammar, cognition, processing, and fixedness all interact with the grammar of clause organization to afford quite different real-time processing strategies for calculating the assignment of negative scope in languages with different ‘word order’ norms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it