Engaging Seniors through Automatically-Generated Photo Digests from their Families' Social Media
Bibliographic record
Abstract
Seniors are increasingly using the Internet. However, their adoption of available services such as social media is often restricted by their limited experience with new technologies. At the same time, there is significant interest in designing communication applications, especially mobile, that improve seniors' social connectedness. These are mostly implemented as dedicated social networking tools for seniors and their families. A barrier to the full adoption of such tools is the requirement for younger family members to actively manage a platform parallel to the social media tools they already use (e.g., Facebook). We propose PhotoDigest -- a user-centred application that allows seniors to passively engage in their families' social media activities. PhotoDigest automatically harvests families' Facebook photo posts and delivers them to seniors as weekly digests. We conducted a preliminary deployment study and show that PhotoDigest is easily adopted by seniors, does not interfere with younger generations' life routines, and enhances the entire family's social connectedness.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".