ASIS&T online education initiatives: Driving the future
Bibliographic record
Abstract
Abstract This panel provides an update for ASIS&T members on the activities of the Webinar Task Force and the Online Education Task Force to increase online communication and education efforts within the Society. Both task forces were formed by presidential appointment in 2011 with the goal of expanding the involvement of ASIS&T in the provision of online educational offerings. In addition to expanding webinar offerings, an organizational emphasis on online communication and education drives increased networking opportunities and ensures that members remain connected to the Society between annual meetings. Panel presentations include comments on the context of online education generally, insight into the background and context of the ASIS&T online education initiative, updates on the results and ongoing efforts of the task forces, and a perspective on the future and potential of online education within ASIS&T. Sponsors SIG/ED and the ASIS&T Online Education Task Force Conference Track TRACK 3, Innovation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".