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Evaluating community capacity

2002· article· en· W2163602242 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

VenueHealth & Social Care in the Community · 2002
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCapacity buildingPsychological interventionRanking (information retrieval)Set (abstract data type)Strengths and weaknessesPromotion (chess)Scale (ratio)Computer scienceData sciencePsychologyGeographyMedicinePolitical scienceMachine learningSocial psychologyEconomic growthNursingEconomicsCartography

Abstract

fetched live from OpenAlex

The aim of the present study was to examine the convergence of two approaches used to assess community capacity in health promotion interventions. One was used to examine women and men in rural communities in Fiji, and the other to study women only in rural communities in Nepal. Both approaches used a set of 'capacity domains', a ranking scale and a means of visually representing the findings. The experiences of using each approach, and the strengths and weaknesses of using rating scales and the 'capacity domains' to assess community capacity are discussed. The use of visual representations of community change, in particular the 'spider web' approach, are also discussed. The capacity building 'domains' presented in this study are robust and capture the essential qualities of a 'capable community'. 'Parallel tracking' of the domains allows programmes themselves to be viewed as a means to the end of building community capacity. These approaches provide a useful new dimension to programme evaluation.

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)0.027
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0320.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.017
Insufficient payload (model declined to judge)0.0010.000

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 head0.627
GPT teacher head0.571
Teacher spread0.056 · 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