Cross-linguistic dataset of force-flavor combinations in modal elements
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 We present a cross-linguistic dataset of force-flavor combinations in modal elements, which currently contains information on modal semantics in 24 languages and is accessible at https://github.com/EdinburghMeaningSciences/modals_database . We discuss theoretical motivations for constructing the dataset, the data collection methodology, as well as the design and the format of the dataset. We also present four case studies using the data: (i) assessment of cross-linguistic generalizations on force/flavor variability; (ii) exploration of generalizations in the lexicalization of negative modality; (iii) investigation of the typology of the morphological encoding of modal strength; and (iv) examination of how future contributes to modality. These case studies illustrate that the dataset supports in-depth assessment of potential cross-linguistic generalizations as well as theory-informed investigations of cross-linguistic variations in modal semantics.
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 | 0.001 | 0.007 |
| 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) | 0.001 | 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