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
This article argues for a dependency between structural Case and phasal domains and against Case values as intrinsic properties of (C)-T and (v*)-V. Rather, Nominative or Accusative values are derived compositionally from properties of the entire Probing domain: (i) Nom occurs whenever the Probing domain is specified as [uD, uf/p], while (ii) Acc is assigned if the Probing domain is specified as [uD]. The presence of a [uCase] feature is assumed on all DP arguments, whether null or overt. However, after Case valuation, DPs with inherent intensions and extensions will be lexicalized but variables, such as PRO, will not. The analysis focuses on DP subjects (both lexical and PRO) in non-finite CPs, and relies on availability of null expletive pro as a UG primitive. It assumes Chomsky’s Feature Inheritance Model (Chomsky 2007, 2008, Richards 2007), default Case as in Schütze (1997, 2001), as well as Distributed Morphology (Halle and Marantz 1993, Embick 2007). It aligns with views where the Case Filter, while syntactically relevant (Legate 2008), is a PF constraint (Lasnik 2008, Sigurðsson 2008).
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 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