Rising above a crisis: Resilience processes and community well-being
Bibliographic record
Abstract
Background The closure of the North Atlantic cod fishery in 1992 has had devastating economic, social and health impacts on coastal communities in Newfoundland and Labrador. However, considerable variability in adaptation has been noted between communities that were formally dependant on the fishery. Aim This thesis builds on previous research by exploring the community-level social and economic processes that contribute to the variability in adaptation measured through an expansive conceptualization of community well-being. Method Two communities differing in employment recovery during the 1990s were selected for multi-method case studies. Quantitative and qualitative data on community well-being, social processes (social capital), and economic processes (local economic development) were integrated into the analysis. Results Ratings of most community well-being dimensions were generally positive in both communities. However, Dorytown residents reported less alcohol abuse, less crime, greater ability to be involved in decision-making, greater satisfaction with community characteristics such as greenery and parks, water quality and services from the local council. Residents of Dorytown were also more hopeful for the future, and perceived greater employment availability in the region. Some mental and physical health indicators were poorer for both communities than for the Province, with the exception of self-rated health and heavy alcohol consumption. Dorytown had lower hospitalization rates than Bigcove, and less modemte and heavy drinking. Community well-being findings for Bigcove were more consistent with documented effects of economic decline. In tenns of economic and social processes, employment in Bigcove had been more dependent on the volatile fishery whereas Dorytown community groups planned and executed an economic development strategy using federal and provincial programming dollars, volunteered labour from the community, and natural resources within the • community. Residents in both communities expressed concerns with employment security in their towns. Interviews suggested that all forms of social capital (bonding, bridging and linking) were associated with greater development of community-controlled economic opportunities and positive social outcomes (youth engagement, public safety) for Dorytown. Other factors such as leadership, human capital (skills and knowledge), and community enabling government policies played a substantial role in outcomes for Dorytown. Conclusion These findings provide some insight as to the community-level processes that underlie certain dimensions of community well-being and demonstrate the benefits of a mixedmethods approach to understanding it. Policy implications include skill-building supports for community development volunteers, and aspiring or existing entrepreneurs, so that they are better equipped to engage with government or other funding bodies, continued support for community development funding programs, and policies that support economic diversification.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".