Providing artifact awareness to a distributed group through screen sharing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the availability of awareness servers and casual interaction systems, distributed groups still cannot maintain artifact awareness – the easy awareness of the documents, objects, and tools that other people are using – that is a natural part of co-located work environments. To address this deficiency, we designed an awareness tool that uses screen sharing to provide information about other people’s artifacts. People see others’ screens in miniature at the edge of their display, can selectively raise a larger view of that screen to get more detail, and can engage in remote pointing if desired. Initial experiences show that people use our tool for several purposes: to maintain awareness of what others are doing, to project a certain image of themselves, to monitor progress and coordinate joint tasks, to help determine when another person can be interrupted, and to engage in serendipitous conversation and collaboration. People have also been able to balance awareness with privacy, by using the privacy protection strategies built into our system: restricting what parts of the screen others can see, specifying update frequency, hiding image detail, and getting feedback of when screenshots are taken.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it