Network-based approaches for evaluating ambient assisted living (AAL) technologies
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
Ambient assisted living technologies could support people experiencing physical or cognitive challenges, to maintain social identities and complex activities of daily living. Although there has been substantial investment in developing ambient assisted living innovation, less effort has been devoted to understanding how to evaluate the impact of ambient assisted living on physical and mental health. Taking a theory-based evaluation approach, we suggest firstly that ambient assisted living technologies rely on networks of people and organizations to function, and secondly, analysing the changing structure of networks can bridge the gap between socio-technological change and individual-level capabilities. We present conceptual arguments for taking a network perspective in ambient assisted living evaluations, illustrated with examples from our own group’s work on technology use among older people with cognitive impairments. We then discuss the different types of network-based evaluation approaches available, their theoretical assumptions, and the sort of research questions they could address.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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) | 0.000 | 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