Integrated Collaborative Tools
Bibliographic record
Abstract
Previous reports in this series have featured examples of integrated products that combine into a single software package, techniques offered individually by other products.Increasing acceptance of online collaboration is generating interest in such tools on the part of product developers and users.The distance education (DE) market is now awash with integrated products involving methods ranging from the relatively standard text-based conferencing to synchronous and asynchronous audio and video conferencing techniques.Integrated products typically add a range of ancillary tools to these main features (e.g., whiteboards, polling methods, file sharing and email capability).When choosing an appropriate product for DE usage it is important to discern which of the multitude of features are essential in different situations.The current study examines five contrasting integrated products from the DE user's perspective.
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 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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 0.020 |
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".