Bibliographic record
Abstract
It is our great pleasure to welcome you to the 1st Workshop on Education: Teaching Digital Literacies associated with WWW 2016.The dynamics of Web Education and Digital Literacies are among today's most important issues surrounding the development of the Web as an efficient, safe and universal information system.A wide range of disciplines including sociology, economics, political studies, health and management science have integrated courses and specializations to teach about the Web, its nature, its realities, its impact its evolution and its integration into every dimension of human activity.The workshop will gather a very broad community of participants: professors involved in digital literacy programs or courses, consultants empowering employees in a company, students or faculty in an interdisciplinary program or activists in an NGO teaching the Web to kids.The call for short papers attracted submissions from Asia, Europe and Canada. The program committee has reviewed and accepted 7 submissions.The workshop will also be preceded and followed by online activities on the Bookwitty.com platform. These activities aim to not only strengthen links within the Web Education Community, but also to gather and present the outcomes of the workshop.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.867 | 0.775 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".