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 dissertation provides an account of stress flexibility in English. Stress is flexible in the sense that words that apparently have the same segmental composition, such as <italic>Canada</italic> and <italic>banana </italic>, may differ in their stress patterns. Unlike current approaches (Halle & Verganud 1987; Hayes 1995; Halle 1998; Hammond 1999) which consider only some stress patterns to be regular and all the rest exceptional, the present proposal views all words as regular and develops a theory that accommodates this view. The theory is based on surface well-formedness constraints (T ROCHEE, FOOTBINARITY, PRE-P ARSE-2, and WEIGHT-STRESS), silent beats, and dual-counting foot structures. The advantages of this approach are numerous. First, the theoretical constructs are universal, i.e. have few exceptions. Second, the analysis is simpler in as much as it makes fewer assumptions. Third, the assumptions have all been proposed for English by others in the field.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 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