La formation documentaire en temps de pandémie : les webinaires matinaux
Bibliographic record
Abstract
Le premier confinement dû au Covid-19 a influencé la manière dont la Bibliothèque des lettres et sciences humaines de l’Université de Montréal a rempli sa mission de formation aux compétences informationnelles. Il nous a poussés à nous adapter rapidement en évaluant nos anciennes manières de faire. Le résultat le plus marquant a été la création d’une offre quotidienne de webinaires matinaux ouverts à tous. Nous avons saisi cette opportunité pour expérimenter et tester des innovations correspondant à nos valeurs d’excellence, de bienveillance et d’ouverture. Leur succès a permis la transformation de notre offre de formations libres en mettant l’accent sur des notions avancées et plus diversifiées.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".