Covert Pied-Piping in English Multiple <i>Wh</i>-Questions
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
In this article, we argue for the existence of covert pied-piping in wh-questions through a previously unnoticed pattern of intervention effects in Superiority-obeying English multiple wh-questions. We show that the preference of covert pied-piping, unlike that of overt pied-piping, is for movement of larger constituents. We argue that this discrepancy stems from conflicting requirements of PF and LF: overt pied-piping feeds both LF and PF, but covert pied-piping feeds LF only. The study of covert pied-piping thus reveals the true preference of LF and narrow syntax with regard to pied-piping: larger pied-piping constituents are preferred over smaller ones. This preference can be overridden by certain PF constraints that apply to overt pied-piping.
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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 | 0.020 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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