Bibliographic record
Abstract
The paper investigates the root suppletion phenomena with its direct relation to the theory of allomorphic locality as it is couched in the Distributed Morphology (DM) framework (Halle & Marantz 1993, 1994) and its recent developments. The paper covers the suppletion phenomena of two varieties, those conditioned by the number of an internal argument and tense-aspect-mood (TAM) features of functional heads merging above roots. The empirical data is brought up to support the main claim that the suppletion of verbal roots can be conditioned not only by the most local elements such as the number of the internal argument, but it can also be triggered by the TAM features of the functional heads which are outside of the XP boundary where the roots are merged (Harley et al. 2009, Bobaljik 2012, Harley 2015 among others). To account for the TAM-conditioned suppletion, the paper is using the phase-theoretic approach following Chomsky (1999) and Embick (2010) by positing a variety of non-cyclic heads merging above roots that render the interaction between TAM features and roots possible even though some of the intervening heads between roots and these features may be overtly realized. The paper arrives at the conclusion that the suppletion can still be triggered by the local material converging with other authors mentioned above.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".