Marginal contrasts and the Contrastivist Hypothesis
Bibliographic record
Abstract
The Contrastivist Hypothesis (CH; Hall 2007; Dresher 2009) holds that the only features that can be phonologically active in any language are those that serve to distinguish phonemes, which presupposes that phonemic status is categorical. Many researchers, however, demonstrate the existence of gradient relations. For instance, Hall (2009) quantifies these using the information-theoretic measure of entropy (unpredictability of distribution) and shows that a pair of sounds may have an entropy between 0 (totally predictable) and 1 (totally unpredictable).We argue that the existence of such intermediate degrees of contrastiveness does not make the CH untenable, but rather offers insight into contrastive hierarchies. The existence of a continuum does not preclude categorical distinctions: a categorical line can be drawn between zero entropy (entirely predictable, and thus by the CH phonologically inactive) and non-zero entropy (at least partially contrastive, and thus potentially phonologically active). But this does not mean that intermediate degrees of surface contrastiveness are entirely irrelevant to the CH; rather, we argue, they can shed light on how deeply ingrained a phonemic distinction is in the phonological system. As an example, we provide a case study from Pulaar [ATR] harmony, which has previously been claimed to be problematic for the CH. This article is part of the special collection: Marginal ContrastsNote: Correspondence can be addressed equally to Daniel Currie Hall (daniel.hall@utoronto.ca), Kathleen Currie Hall (kathleen.hall@ubc.ca).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".