Mixing Methods and Sciences: A Longitudinal Cross-Disciplinary Mixed Methods Study on Technology to Address Social Isolation and Loneliness in Later Life
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 a growing interest in longitudinal mixed methods research, the literature offers few examples of complex designs. To evaluate a communication-based technology to address social isolation and loneliness in later life, we conducted two long-term studies in aged-care homes. We used a longitudinal convergent mixed methods design and a cross-disciplinary approach that employed techniques from social and computer sciences to ensure a comprehensive evaluation. While cross-disciplinary mixed methods research is also growing, a discussion of its methodological practices, challenges, and strategies is still scarce. This article contributes to mixed methods research by providing lessons learned on how cross-disciplinary mixed studies can be designed and integrated from collection to interpretation, particularly when combining convergent and longitudinal approaches. We also show the value of “design-in-action”—that is, the refinement and adjustment of techniques throughout research, as methods “talk to each other.”
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 | 0.062 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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