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Record W1823758325 · doi:10.1177/160940690700600201

Discovering Voice: A Participatory Action Research Study with Nurses in Uganda

2007· article· en· W1823758325 on OpenAlexaff
Bonnie Fournier, Judy Mill, Walter Kipp, Mariam Walusimbi

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParticipatory action researchCitizen journalismAction (physics)Action researchQualitative researchSociologyReflection (computer programming)Work (physics)Engineering ethicsPublic relationsPsychologyPolitical sciencePedagogySocial scienceEngineering

Abstract

fetched live from OpenAlex

In this article the authors present findings from a qualitative research study carried out with Ugandan nurses from September 2003 until June 2004. They highlight the process and philosophical basis of participatory action research (PAR) by reflecting on the challenges, opportunities, outcomes, and ethical issues encountered during the conduct of the research. In this study PAR fostered a climate in which nurses could engage in collective reflection on their practice, make sense of their experiences, and thereby change their understanding of their work.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.042
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0240.014
Scholarly communication0.0090.007
Open science0.0030.012
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.967
GPT teacher head0.852
Teacher spread0.116 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations31
Published2007
Admission routes1
Has abstractyes

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