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Record W1505252716

Understanding Community Resiliency in Rural Communities through Multimethod Research

2008· article· en· W1505252716 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsRed Deer PolytechnicQueen's University
Fundersnot available
KeywordsQualitative researchRural communitySociologyPsychologyScale (ratio)Process (computing)Community psychologyCommunity developmentSocial psychologyPublic relationsSocial scienceSocioeconomicsEconomic growthPolitical scienceGeographyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Community resiliency is a theoretical framework and social process that attempts
\nto explain how communities address adversity. Generating information about this
\nconcept has largely been accomplished through qualitative research methods and
\nthe development of the Resiliency Scale, which was based upon previous
\nqualitative research on the topic. A multimethod study was used to explore
\ncommunity resiliency in two rural communities and one urban neighborhood. In
\nthis article we specifically examine: “What are the merits of employing different
\nresearch methods to explore community resiliency and health status?” Qualitative
\ninterviews, a household survey, and analysis of provincial health databases were
\nall used. The understanding of community resiliency as identified from each of
\nthese three methods as well as a discussion of the advantages and disadvantages of
\neach method is presented.

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.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.002
Open science0.0030.001
Research integrity0.0000.002
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 head0.468
GPT teacher head0.352
Teacher spread0.116 · 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