More than a Meeting: Identifying the needs of the community-based seniors’ services sector with a research partnership
Bibliographic record
Abstract
Abstract Background : Through a weakening of the welfare state, many economically developed countries have seen a decline in publicly funded community programming. Within this context of hollowed-out services for community-dwelling older adults, community-based seniors’ service (CBSS) organizations have been increasingly tasked to deliver programs to enable independence, health and social connections for older citizens. In response, CBSS leaders have taken steps to organize as a unified sector and have expanded their partnerships with researchers and universities to enhance and track this work. The primary objective of this study was to capture of the current needs of CBSS leaders in British Columbia, Canada, who attended a seminal event in the CBSS sector’s development – the inaugural Summit on Aging (i.e. the Summit). Hosting and evaluating The Summit was a collaborative effort between CBSS organizations and a university-based research team. The secondary objective of this study was to understand the value of hosting the Summit for those who attended. Methods : We implemented a mixed-method evaluation plan, which included: a pre- (n=79) and post-event online survey (n=76); thematic notes from six breakout sessions, 4 large group sessions, and ethnographic observations from each day of the Summit; and a 6-month post-Summit semi-structured telephone interview (n=22). Results : Summit delegates identified key opportunities to strengthen the CBSS as a sector, including enhanced collaboration; improved mechanisms that foster connecting and collaborating; and more resources (i.e. funding, trained personnel) to increase their capacity to deliver respond to current and future service demands. Overall, participants found the Summit to be a worthwhile event; it provided a venue to strategize as to how to meet sector needs. Conclusions : In the context of aging societies and a decline in direct support from the state, we must more meaningfully invest and support the vital work that CBSSs are increasingly providing to older citizens. Here we determine key needs within the CBSS and highlight how an event such as the Summit, can help facilitate collaboration, connections and resources. Our community-based research partnership maximized our collective efforts to robustly capture the changing needs of an evolving sector.
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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 | 0.065 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.006 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".