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Record W2857807603 · doi:10.1002/jgf2.187

Participatory research—A modernizing science for primary health care

2018· article· en· W2857807603 on OpenAlexaff
Neil Andersson

Bibliographic record

VenueJournal of General and Family Medicine · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsMcGill University
Fundersnot available
KeywordsParticipatory action researchGeneral partnershipMedicineToolboxParticipatory GISPublic relationsCommunity-based participatory researchCitizen journalismHealth careContext (archaeology)Health services researchSociologyNursingPublic healthPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Participatory research is the science of partnerships underlying research, concerned with research governance, ownership of research products, and relationships behind research objectives and methods. The common strand behind the quite different schools of participatory research is that research should be in respectful partnership with people; it is not about researchers working on, for, or about people. Modern participatory research embraces different philosophies through several applications. The first application addresses research objectives, with participation at different points in the research cycle. Second, modern participatory research is relevant in adaptive management, including management of primary health care. Third, participatory research is a tool for patient engagement and patient‐centered outcomes in the clinical context. A fourth application is participatory research as an intervention: Participatory research moves people, and it mobilizes resources and can thus be pivotal to sustainability and for health‐promoting intersectoral linkages. As primary health care is a family medicine responsibility, participatory research offers family medicine a valuable toolbox complementing the accepted clinical toolboxes. Through shared identification of problems and decisions about solutions, participatory research increases participant capacity to identify and address their own issues. Among clinicians, it enhances professional practices. In the bigger social picture, all this promotes social justice, self‐determination, and knowledge utilization.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.674
GPT teacher head0.578
Teacher spread0.096 · 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 designNot applicable
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

Citations75
Published2018
Admission routes1
Has abstractyes

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