Proceedings of Ninth Meeting of the ACL Special Interest Group in Computational Morphology and Phonology
Bibliographic record
Abstract
Welcome to the ACL Workshop on Computing and Historical Phonology, the 9th Meeting of ACL Special Interest Group for Computational Morphology and Phonology, a meeting held in conjunction with the 45th Meeting of the ACL in Prague. An introductory article explains our motivation for holding the workshop, which attracted 16 submissions, all but one of which is included in this volume of proceedings. We are gratified not only by the level of interest, but also by the quality of submissions we received. We hoped to attract interest not only in the computational linguistics community sensu stricto but also in the broader linguistics community, and in the group of geneticists who have begun to apply phylogenetic analysis to linguistic data. As the reader may verify in these proceedings, we were not disappointed in this hope. Perhaps it is worth adding that, while we are in principle interested in further meetings of this sort, there are at the time of this writing no concrete plans for follow-ups.
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.
How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".