Prepositional adverbials in French in Quebec (Saguenay–Lac-St-Jean). Appendix: Statistical Measures (Project Materials)
Bibliographic record
Abstract
These project materials are to be understood as an appendix to a book chapter by Inka Wissner, Inka and Melissa Gagnon, “Adverbials with preposition and adjective in Eastern Quebec (Saguenay–Lac-St-Jean)”, forthcoming in De Gruyter. They provide detailed tables illustrating the exact measures realized on Quebec French data retrieved by Melissa Gagnon during sociolinguistic field work in Saguenay–Lac-St-Jean from 2021 to 2022 with thirty-four informants within the Third Way project on prepositional adverbials from Latin to Romance, a project led by Martin Hummel at the University of Graz (Austria). Measures are realized according to a method prepared from 2020 to 2021 by Wissner and Roy. It has been applied to all Romance languages under study in the Third Way project.
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 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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.084 | 0.008 |
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".