NP ellipsis without focus movement/projections: the role of Classifiers
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
Ellipsis has often been argued to be closely related to concepts generally ascribed to the domain of information structure, notably the notion of Focus. An isomorphic mapping is assumed to exist between the interpretation of the focused element in ellipsis and syntactic positions licensing the ellipsis site. This is reflected in the literature on Noun Phrase Ellipsis (NP Ellipsis), in which focus is among the licensing mechanisms suggested to account for the derivation of ellipsis. In these focus-based analyses of (NP) ellipsis (as in, e.g., Corver and van Koppen unpub. ms., Eguren 2010 and Ntelitheos 2004), information-structural positions have been proposed to be an integral part of the syntactic structure. The focus approach to NP Ellipsis, employing specific focus projections, thus differs substantially from previous approaches to NP Ellipsis, in which the licensors were taken to be (i) agreement (Lobeck 1995, Kester 1996, among others), or – related to agreement – (ii) word-markers (e.g. Bernstein 1993), in the domain of morphosyntax; or, in a rather semantic approach, the licensor was taken to be (iii) partitivity (Sleeman 1996, among others).
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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