MétaCan
Menu
Back to cohort
Record W2319442426

The Adaptation of Rural Communities to Socio-Economic Change: Theoretical Insights from Atlantic Canada

2013· article· en· W2319442426 on OpenAlexaffvenueabout
Stacey Wilson-Forsberg

Bibliographic record

VenueJournal of rural and community development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSocial capitalEconomic growthAdaptation (eye)Face (sociological concept)Psychological resilienceCapital (architecture)Resource (disambiguation)Adaptive capacitySociologyPolitical scienceEconomicsGeographyClimate changeEcologySocial science
DOInot available

Abstract

fetched live from OpenAlex

Why do certain rural communities have the capacity for renewal and innovation in the face of transformation, while others stagnate, decline, and die out? What factors are involved in the resiliency of the former communities, and what conditions cause the latter to falter in their capacity for survival? With the hope of gaining valuable insight in support of the economic development agenda of Atlantic Canada, this article reviews the definitional and theoretical literature surrounding the adaptation of rural communities to changes brought about by the transition to knowledge-based economies. The article defines and discusses the merits of community resiliency, community assets, community capitals, and social capital, placing these concepts within a larger entrepreneurial social infrastructure framework. The history and socio-economic realities of the four Atlantic Canadian Provinces are woven together in an effort to keep the literature review and arguments as relevant as possible to the current circumstances of the region. Keywords: Rural Atlantic Canada; natural resource dependence; economic development; community resiliency; community assets; social capital; entrepreneurial social infrastructure

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.256
Teacher spread0.224 · 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

Citations10
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueJournal of rural and community developmentSame topicSocial Sciences and GovernanceFrench-language works237,207