From Thumbs to Fingertips: Introducing Networked Digital Video to Online Learning
Bibliographic record
Abstract
We have turned the corner in 2005, putting video programs on the library shelves behind us and video objects online at our fingertips. Recent breakthroughs in the educational video distribution industry are removing the hard plastic wrapper from video programs, and controls on the use of video are giving way to new freedoms. Now with enabling rights of use and IT applications for users, video is being reintroduced to curriculum as an information resource and as a methodology. Video, now that it is available in digital form online, is finally joining other media in a rich mixture of learning objects for e-learning. There is a substantial difference, however, in the role played by digital video in this mix. In the multipleformat universe of educational objects, video is a new kind of manipulative with which the learner creates meaning and constructs knowledge. This discussion offers a brief overview, or perhaps a “practitioners’ alert,” about what we can expect from video once we have transferred it from our library shelves to our servers.
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 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".