The typological effects of ABC constraint definitions
Why this work is in the frame
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Bibliographic record
Abstract
Recent work under the theoretical banner of Agreement by Correspondence (ABC) has produced a variety of different – and sometimes contradictory – formulations of the constraints central to this framework. In OT, the effects of such definitional choices come out in the factorial typologies they predict. Yet knowing what languages a theoretical system derives is insufficient unless we know why it does so. This requires analysis of the internal ranking structures of the typology itself. This paper compares the typologies produced under different proposed modifications to the main ABC constraints. We analyse the typologies in Property Theory, a theory of typological organisation in OT. Our analyses show that all variations have a common core structure, and that differences in their factorial typologies reduce to differences in how this common structure expands and iterates for different features. This allows for precise delineation of how and why different ABC constraint definitions affect typologies.
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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 | 0.001 |
| 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 | 0.002 |
| 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