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Record W2948030860 · doi:10.54656/zryk7626

“We Know We Are Doing Something Good, But What Is It?”: The Challenge of Negotiating Between Service Delivery and Research in a CBPR Project

2014· article· en· W2948030860 on OpenAlexaboutno aff
Fay Fletcher, Brent Hammer, Alicia Hibbert

Bibliographic record

VenueJournal of Community Engagement and Scholarship · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
Fundersnot available
KeywordsCommunity-based participatory researchNegotiationParticipatory action researchSociologyService (business)Public relationsAgency (philosophy)Process (computing)Service delivery frameworkBusinessPolitical scienceSocial scienceMarketingComputer science

Abstract

fetched live from OpenAlex

Engaging communities throughout the research process and responding to community priorities results in constant negotiation between service and research. Community-based participatory research has well established principles intended to guide both the process and goals of research with community. The authors contribute to the body of literature that speaks to the challenge of achieving CBPR ideals amidst the complexity of community realities. When university-based research is aligned with community-based service delivery, at least three sets of expectations must be balanced - those of the community, the university, and the funding agency. The complexity of achieving balance between the ideal and the reality of CBPR, and balance between service delivery and research, were explored using a cyclical process of debriefs throughout the delivery of a youth life skills program with Métis Settlements in Alberta. The value of the process and lessons learned are 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.

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)0.100
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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 score0.103
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.008
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 head0.827
GPT teacher head0.641
Teacher spread0.186 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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