An exploratory study on renovations of a special needs dementia unit
Bibliographic record
Abstract
In the summers of 2017 and 2019, a team of researchers from the Centre on Aging at the University of Manitoba conducted a research project on the renovations to the special care unit at Riverview Health Centre. During this project, we were fortunate to have many staff, family and residents participate in the various aspects of the project. We are grateful to all participants who were very generous with their time. Please note that all elements of the renovated spaces were not fully functional during this research project. This was due in part to technology implementation and renovation delays at Riverview. We had hoped to do an evaluation of all the new spaces in 2020 with family and staff. However, the pandemic prevented this from happening. This means that we were not able to assess the use of the new pavilion and courtyard spaces. The completed renovation and technology elements included: smaller dining and lounge spaces, new lighting, image films on doors (resident rooms and exit), flooring and wall coverings, murals, staff communication technology, and re-location of the nursing station. This summary will highlight research findings associated with the new elements and how they impacted residents and staff. Research findings come from surveys, resident statistics, observations of the residents and how the spaces were used. In addition, we made physical measurements of lighting and noise levels.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".