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Record W2580212327

Rising above a crisis: Resilience processes and community well-being

2011· dissertation· en· W2580212327 on OpenAlexaboutno aff
Monique Goguen Campbell

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2011
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
Fundersnot available
KeywordsSocial capitalCommunity resiliencePsychological resilienceExpansiveGeographyMental healthAdaptive capacityConceptualizationSocioeconomicsPolitical scienceClimate changePsychologySociologyEcologySocial psychologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0060.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.266
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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