A critical reflection of an intergenerational, student-led team bringing social robots and research to older adults in the community
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
Knowledge translation and exchange to promote the health and well-being of older adults requires collaborative relationships between researchers and knowledge users. Students are uniquely positioned to engage with the community and bridge these science-practice gaps. In this paper, we highlight key lessons learned from our interdisciplinary and intergenerational team's critical reflections on our experiences and learnings bringing the LOVOT social robot to engagement sessions with older adults in our community. Our critical reflection process followed the reflection framework by Rolfe et al. (2001), guided by three questions: (1) "What?", (2) "So what?," and (3) "Now what?" We conducted thematic analysis on our collective reflections. Three key learnings emerged from our critical reflections: (1) the values of meaningful interactions between older adults in our community and our team; (2) the diversity of backgrounds and perspectives of older adults in our community; and (3) factors that supported or challenged our community engagement sessions. We conclude with six recommendations for future student-led community engagement sessions.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it