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
We examine how one particular coherence relation, Concession, is marked across languages and modalities, through an extensive analysis of the Concession relation, examining the types of discourse markers used to signal it. The analysis is contrastive from three different angles: markers, languages, and modalities. We compare different markers within the same language (but, although, however, etc.), and two languages (English and Spanish). We aim to provide a contrastive methodology that can be applied to any language, given that it has as a starting point the abstract notion of coherence relations, which we believe are similar across languages. Finally, we compare two modalities: spoken and written language. In the analysis, we find that the contexts in which concessive relations are used are similar across languages, but that there are clear differences in the two modalities or genres. In the spoken genre, the most common function of concession is to correct misunderstandings and contrast situations. In the written genre, on the other hand, concession is most often used to qualify opinions.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| 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 it