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Record W4386102386 · doi:10.1136/bmjopen-2022-069680

Employing diffusion of innovation theory for ‘not missing the mass’ in community-engaged research

2023· review· en· W4386102386 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

VenueBMJ Open · 2023
Typereview
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsFoothills Medical CentreUniversity of Calgary
Fundersnot available
KeywordsCommunity engagementPublic relationsParticipatory action researchCitizen journalismRelevance (law)ImmigrationCommunity-based participatory researchSociologyPerspective (graphical)Ethnic groupCommunity organizationMedicineEngineering ethicsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

INTRODUCTION: Engaging with minority communities, such as immigrants and ethnic minorities, often involves adopting top-down approaches, wherein researchers and policymakers provide solutions based on their perspective. However, these approaches may not adequately address the needs and preferences of the community members, who have valuable insights and experiences to share. Therefore, community-engaged approaches, which involve collaborative partnerships between community members and researchers to identify issues, co-create solutions, and recommend policy changes, are becoming more recognized for their effectiveness and relevance. Yet, prevailing community engagement efforts often focus on easily reachable and already engaged segments of the community, sometimes overlooking the broader population. METHODS: When working with immigrant and racialized communities, we encountered difficulties in engaging the wider community through traditional researcher-led approaches. We realized that overcoming these challenges required innovative strategies rooted in community-based participatory research principles and the diffusion of innovation theory. We recognized that a nuanced understanding of the community's dynamics and preferences was crucial in shaping our approach and building trust and rapport with the community members. RESULTS: The need to bridge the gap between researcher-led initiatives and community-driven involvement has never been more pronounced. Our experience, chronicled in this article, highlights the journey of our research program with an immigrant/racialized community. This reflection enhances our comprehension of community engagement that deliberately strives to reach a larger cross-section of the community. By providing practical methods for reaching the broader community and navigating the intricacies of engagement, we aim to assist fellow researchers in conducting effective community-engaged research across various minority communities. CONCLUSION: In sharing our insights and successful strategies for community engagement, we hope to contribute to the field's knowledge. Our commitment to fostering meaningful collaboration underscores the importance of co-creating solutions that resonate with the diverse voices within these communities. Through these efforts, we envision a more inclusive and impactful approach to addressing the complex challenges faced by minority populations.

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)0.557
metaresearch head score (Gemma)0.291
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5570.291
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0030.002
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 head0.979
GPT teacher head0.816
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