What learning Latin verbal morphology tells us about morphological theory
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
Abstract The Classical Latin verb has featured prominently in theoretical morphology. In particular, the notoriously unpredictable forms of the past participles that nevertheless show reliable syncretism with a semantically diverse set of deverbals challenge our notions about the relationship between form and meaning. The various treatments of this system disagree not only in their theoretical building blocks but also in their basic assumptions about what ought to be explained, which makes it difficult to properly evaluate them against one another. This paper aims to empirically motivate the prior assumptions about productivity and arbitrariness that drive these accounts. In applying insights developed for child language acquisition to a large Latin corpus, the theoretical frameworks are compared on equal footing. It becomes clear that the productive past participle forms do not line up well with the frequency-based assumptions of prior accounts and instead mirror the diachronic developments that the system underwent on its path to Romance. A new treatment is proposed to incorporate the acquisition results and to conform with diachronic outcomes. The methods developed here reveal explanatory gaps in the theories that had not previously been appreciated and emphasize the importance of quantitative evidence from a range of sources in future morphological analysis.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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