On the Edge in Rural Canada: The Changing Capacity and Role of the Voluntary Sector
Bibliographic record
Abstract
ABSTRACT Since the 1980s, neoliberal policies have downsized or closed rural and small-town services. In response, voluntary groups have played an increasing role to retain basic supports. How voluntary groups are impacted, and how they react, will affect community development. Drawing upon our research across northern BC and Canada, this article explores the changing role of voluntary groups, with a focus on the structural and institutional barriers impeding their renewal. Our research suggests that voluntary organizations have been diversifying their human and financial capital, expanding partnerships, and developing smart infrastructure to enhance their capacity. More place-based policies and programs are needed to: renew relationships; create synergies; stabilize operations; renew mandates and procedures; develop training supports; enhance development expertise; build diversity, capacity, and support for volunteers; and develop information management systems. Résumé Depuis les années 80, des politiques néolibérales ont entraîné la diminution ou l’élimination de divers services dans les communautés rurales. En conséquence, les groupes bénévoles ont joué un rôle grandissant dans la préservation de services de base. Le traitement des bénévoles et leurs réactions face à ce traitement ont ainsi un impact sur le développement communautaire. Cet article a recours à notre recherche dans le nord de la Colombie-Britannique et ailleurs au Canada pour explorer le rôle changeant des groupes bénévoles dans un contexte où des défis structurels et institutionnels peuvent nuire à leur renouveau. Notre recherche laisse entendre que, pour accroître leurs capacités, les organisations bénévoles sont en train de diversifier leur capital humain et financier, augmenter le nombre de leurs partenariats et développer une infrastructure intelligente. Il faut davantage de politiques et programmes qui tiennent compte du milieu afin de : renouveler les relations; créer des synergies; stabiliser les opérations; reformuler les mandats et procédures; appuyer les activités de formation; accroître l’expertise en développement; augmenter l’aide aux bénévoles ainsi que leur diversité et leurs capacités; et développer de meilleurs systèmes de gestion de l’information.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".