L’accessibilité commence dans la planification : comment développer des sites Web accessibles ? : conférence en ligne de Cédric Anderson (Laboratoire NT2)
Bibliographic record
Abstract
1 L'accessibilit commence dans la planification : comment dvelopper des sites Web accessibles?Confrence en ligne de Cdric Anderson (Laboratoire NT2) 10 juin 2020 Cette confrence s'inscrit dans le cadre d'Interroger l'accs, une srie de confrences et d'ateliers sur l'accessibilit des productions artistique et mdiatique, dveloppe par OBORO et Spectrum Productions avec le soutien du Conseil des arts du Canada.OBORO et Spectrum Productions reconnaissent que leurs activits ont lieu Tiohti:ke, en territoire kanien'keh:ka non cd. (Dbut de la transcription)Bonjour.Mon nom est Cdric Anderson et nous allons voir ensemble aujourd'hui ce qu'est l'accessibilit Web au Qubec.Avant de commencer, j'aimerais remercier le centre OBORO de m'avoir invit et j'espre que la prsentation va vous plaire. l'ordre du jour : Qui je suis et ce que je fais comme travail. L'tat des lieux de l'accessibilit Web au Qubec. Le WCAG 2.0, qui est le protocole utilis au Canada. WAI-ARIA, qui sont des aides pour les balises HTML. Le HTML accessible. Les outils en ligne qui nous permettent de vrifier qu'un site est bel et
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.055 | 0.010 |
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".