Bibliographic record
Abstract
This article provides an insight into the complex issue of producing the first edition of the dictionary of Valoc’ – a variety of Lombard spoken in Val Masino, lower Valtellina (northern Italy). This new lexicographic project was initiated in 2017 and is called Vocabolär del Valoc’ de la Val Mäśen – VVV [Vocabulary of Valoc’ of Val Masino]. Our research team works on the material of an unpublished dictionary based on interviews collected in the 1960s and 1970s. Our methodological approach is both that of dialectology and sociolinguistics as we complement our study with observations and interviews among Valoc’ speakers of different ages, genders and occupations, to see how it is still used today. Moreover, our approach allowed us to observe the process of the transmission of Valoc’ from one generation to another as well as some discourses among speakers on its uses. In conclusion, this contribution brings us to reflect on how the new “global” society may influence the process of transmission of this endangered language which needs to be revitalised. Interventions at primary and secondary school have been offered in order to introduce Valoc’ as a language of everyday communication and not only as the “dialect” of pupils’ grandparents. We examine the importance of developing a dictionary in order to promote a norm of reference in writing as a way to preserve Valoc’ for the future.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".