An investigation into the use of smart home devices, user preferences, and impact during COVID-19
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
With the goal of designing smart environments that can support users' physical/mental well-being, we studied users' experiences and different factors that can influence success of smart home devices through an online study conducted during and after the COVID-19 restrictions in June 2021 (109 participants) and March 2022 (81 participants). We investigated what motivates users to buy smart home devices, and if smart home devices may have the potential to improve different aspects of users' well-being. As COVID-19 emphasized a situation where people spent a significant amount of time at home in Canada, we also asked if/how COVID-19 motivated purchase of smart-home devices and how these devices affected participants during the pandemic. Our results provide insights into different aspects that may motivate the purchase of smart home devices and users' concerns. The results also suggest that there may be correlations between the use of specific types of devices and psychological well-being.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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