Fusional morphology, metasyncretism, and secondary exponence
Bibliographic record
Abstract
Using Latin as a case study, we show that Lexical-Realizational Functional Grammar (a union between a morpheme-based realizational morphology and the nonderivational, constraint-based syntactic framework of Lexical-Functional Grammar) is able to offer insights into two fundamentally important morphological phenomena. The first of these is metasyncretism, which is of particular interest because it is a (putative) paradigmatic effect, yet LRFG does not have paradigms as theoretical objects. Syncretism is captured via cascading macros (i.e., templates), such that a macro for one case value may also call another macro with a different case value, leading to case containment which models a feature hierarchy. We also use the same approach for gender and number. Metasyncretism is handled through a single vocabulary item mapping to a disjunction of two or more possible exponents. The second phenomenon of interest is secondary exponence (or morphological conditioning). This is handled through the addition of constraints to the (relevant) vocabulary items corresponding to their conditioning environments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".