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Record W1996555243 · doi:10.1093/cdj/bsp041

Organizing community-based research knowledge between universities and communities: lessons learned

2009· article· en· W1996555243 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCommunity Development Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of British ColumbiaPositive Living Society of British Columbia
Fundersnot available
KeywordsParticipatory action researchGeneral partnershipSociologyCommunity organizationService-learningAction researchCitizen journalismCommunity developmentPublic relationsPedagogyPolitical science

Abstract

fetched live from OpenAlex

This article explores teaching, learning, and research that dynamically engages students, community workers, community members, and academics in a type of knowledge organization: the practice of community-based research (CBR). This case study details a university course in which participants (i) work together in CBR activities that foster partnership between universities and agencies in the non-profit sector, particularly AIDS service organizations in the city of Vancouver, BC, (ii) build bridges between classroom- and community-grounded knowledges and personal experience, and (iii) explore the learning and ethical underpinnings of this experience. We argue that the interaction between students, professors, and community-based organizations that results from CBR and participatory action research provides a framework for community development and the transfer of knowledges, skills, and practices between communities and individuals.

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)0.028
metaresearch head score (Gemma)0.000
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 score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0460.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.011
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 head0.476
GPT teacher head0.461
Teacher spread0.015 · 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