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Record W2033206277 · doi:10.1177/1090198105285927

Who Benefits From Community-Based Participatory Research? A Case Study of the Positive Youth Project

2006· article· en· W2033206277 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 Education & Behavior · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsWellesley Institute
Fundersnot available
KeywordsParticipatory action researchCommunity-based participatory researchAnonymityPublic relationsFraming (construction)BusinessEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Community-based participatory research (CBPR) has evolved as a popular new paradigm in health research. This shift is exciting, yet there is still much to discover about how various stakeholders are affected. This article uses a critical social science perspective to explore who benefits from these changes through an analysis of a CBPR case study (The Positive Youth Project). Two major categories of beneficiaries emerged: the research itself and the partner-stakeholders. The benefits, however, were not gained without substantial human resource investment, nor were they necessarily equitably spread. Participation costs included heavy demands of time, an added burden of work, frustration with the process, missing other opportunities, risking loss of anonymity, and loss of control. Care needs to be taken to ensure that concrete benefits accrue for all project partners and costs are minimized. Another way of framing benefits is to look at the community capacities built to address future health and social issues.

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)0.008
metaresearch head score (Gemma)0.001
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 score0.518
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.892
GPT teacher head0.730
Teacher spread0.162 · 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