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Record W2094211046 · doi:10.1080/15575330109489681

Capacity for Community Development: An Approach to Conceptualization and Measurement

2001· article· en· W2094211046 on OpenAlexaffabout
Scott McLean, Lori S. Ebbesen, Kathryn Green, Bruce Reeder, David Butler-Jones, Sheilagh Stee

Bibliographic record

VenueCommunity Development Society Journal · 2001
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsConceptualizationDevelopment (topology)SociologyComputer sciencePsychologyManagement scienceMathematicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The concept of "capacity" has generated substantial interest among community development practitioners and scholars. This article describes our efforts to understand and measure health promotion capacity in Saskatchewan, and encourages readers to think about the usefulness of this concept in other community development contexts. We conceptualize capacity as a set of knowledge, skills, commitments, and resources required by individuals and organizations to effectively plan, implement, and evaluate health promotion activities. We initially operationalized and measured capacity through survey instruments designed to elicit responses from health promotion practitioners and leaders of regional health care organizations. After the initial administration of these two surveys, and following additional qualitative consultations with respondents to the surveys, we developed "capacity checklists" as practical tools to help practitioners and leaders assess their individual and organizational capacity for health promotion work. The ability to better understand and measure capacity enables community developers to more effectively pursue continuing education and organizational development efforts.

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)0.020
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 score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0280.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.005
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 head0.395
GPT teacher head0.429
Teacher spread0.034 · 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

Citations13
Published2001
Admission routes2
Has abstractyes

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