Sharing Domestic Life through Long-Term Video Connections
Bibliographic record
Abstract
Video chat systems such as Skype, Google+ Hangouts, and FaceTime have been widely adopted by family members and friends to connect with one another over distance. We have conducted a corpus of studies that explore how various demographics make use of such video chat systems in which this usage moves beyond the paradigm of conversational support to one in which aspects of everyday life are shared over long periods of time, sometimes in an almost passive manner. We describe and reflect on studies of long-distance couples, teenagers, and major life events, along with design research focused on new video communication systems—the Family Window, Family Portals, and Perch—that explicitly support “always-on video” for awareness and communication. Overall, our findings show that people highly value long-term video connections and have appropriated them in a number of different ways. Designers of future video communication systems need to consider: ways of supporting the sharing of everyday life rather than just conversation, providing different design solutions for different locations and situations, providing appropriate audio control and feedback, and supporting expressions of intimacy over distance.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".