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Record W2267119301

Supportive communities and a sense of belonging in rural and non-rural communities in Canada

2015· article· en· W2267119301 on OpenAlexaffvenueabout
E. Dianne Looker

Bibliographic record

VenueJournal of rural and community development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsRural communityFeelingRural areaSense of communityBureaucracyAffect (linguistics)Diversity (politics)Economic growthRural sociologySocioeconomicsSociologyRural developmentPolitical sciencePsychologyGeographySocial psychologySocial scienceAgriculture
DOInot available

Abstract

fetched live from OpenAlex

This analysis examines where people turn in times of change, and factors that affect one's sense of belonging to a community. Cycle 22 of the Canadian General Social Survey provides data on rural and non-rural areas; the New Rural Economy Project has detailed information on twenty rural communities. Many of the changes participants experienced in the last year had neutral or positive effects. Family and friends are the principal source of support in both rural and non-rural communities. (Bureaucratic and informal associative networks are important for fewer.) Like rural participants, non-rural participants also report they belong to their community, a feeling that is stronger in rural communities which are open to diversity, have many, effective leaders, and encourage community participation. Keywords: youth, community attachment, rural, social networks, social support

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.261
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2015
Admission routes3
Has abstractyes

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