Communication Mechanisms for Delivering Information to Seniors in a Changing Small Town Context
Bibliographic record
Abstract
The settlement landscape of northern British Columbia is comprised of many small and dispersed resource towns that were designed through the 1960s and 1970s to attract young labour and their families. Over the past three decades, industrial restructuring and labour shedding technologies has prompted an out-migration of young families and an ageing-in-place of the existing workforce. The retirement experiences of older residents who remain in these places, however, have been challenged by neoliberal-inspired „structural? changes in services and supports. The constant change in services, and limited flow of information about such changes, can result in frustration amongst older residents attempting to access services and supports. Drawing upon 74 key informant interviews with seniors and service providers in Terrace, BC, we explore problems associated with communication strategies that limit seniors? access to needed supports. Our findings provide a foundation to develop responsive institutional capacities and strengthen new multi-faceted communication approaches to address seniors? needs in rapidly changing places. As there is great diversity amongst seniors in small towns, it will be important for service providers to use multiple communication tools, engage in two-way dialogue activities, and work collectively to collate information about local and regional service supports as part of an efficient and effective communications strategy. Keywords: resource towns, seniors, services, restructuring, communication, Canada
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".