Geriatric Cooperatives in Southwestern Ontario: A novel way of increasing inter-sectoral partnerships in the care of older adults with responsive behaviours
Bibliographic record
Abstract
Established in 2010, Geriatric Cooperatives support the evolving Behavioural Supports Ontario (BSO) programme in the South West Local Health Integration Network. Geriatric Cooperatives bring together members representing relevant cross-sectoral services and are tasked with identifying system gaps associated with the BSO target population as well as developing work plans specific to their local area, leveraging local capacity, and co-ordinating and improving linkages between sectors and services. The purpose of this study was to evaluate the partnerships formed over time within these Cooperatives in order to inform their ongoing development and sustainability. In 2012 and in 2015, Geriatric Cooperative members were invited to complete the Partnership Self-Assessment Tool (PSAT), a valid and reliable tool for evaluating collaborative processes and identifying areas in need of improvement. Scoring the PSAT involves the calculation of mean scores (ranging from 1 to 5) for each of six dimensions describing effective collaboration; higher mean scores reflect better functioning. Two psychometrically sound versions of the PSAT exist; the shorter version (PSAT-S) scores fewer items in three dimensions. Survey response rates for the three Cooperatives that were evaluated in both 2012 and 2015 were 70% in 2012 and 36% in 2015; 57% of members who completed the survey in 2015 were new Cooperative members. Both years, more than 25% of respondents selected "don't know" for three of the nine items used to score the administration and management dimension. Both PSAT and PSAT-S mean dimension scores across both years reflected that more effort is needed to maximise collaborative potential. Use of the PSAT has promoted a better understanding of how partnerships are functioning. Knowledge of where more work is required along with effective strategies to overcome weak areas and gaps in functioning has the potential to ensure that these Cooperatives are successful.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".