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Record W4402961169 · doi:10.1108/qrj-03-2024-0069

Three days together around the table: using the group analysis method to value the expertise and lived experiences of key voices to innovate solutions

2024· article· en· W4402961169 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

VenueQualitative Research Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité de SherbrookeUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsKey (lock)Table (database)Value (mathematics)SociologyGroup (periodic table)Lived experiencePsychologyMathematicsComputer scienceStatisticsData miningPsychoanalysisPhysicsOperating system

Abstract

fetched live from OpenAlex

Purpose This paper presents the use of the Group Analysis Method (GAM), an innovative method developed in a francophone context, to discuss issues related to the services offered in the field of addiction in Quebec’s Indigenous communities and to identify perspectives for innovative solutions. Design/methodology/approach This article begins with a detailed description of the method’s phases and steps based on the French-language writings of the developers of the GAM. The authors then illustrate a concrete example of how this method has been applied to addiction intervention stakeholders in Indigenous communities in Quebec (Canada), highlighting the type of results possible. Findings The strengths and weaknesses of the GAM for addressing sensitive issues in an Indigenous context are discussed. Recommendations for further integration of the Indigenous perspective into the approach are proposed. Originality/value This article presents a relevant qualitative method for co-constructing solutions with groups which, to our knowledge, has not been described in the English-language literature. In the light of their experience in an Indigenous context, the authors adopt a critical perspective, demonstrating the relevance of the method and suggesting adaptations to ensure an equitable distribution of power through the process.

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)0.054
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0540.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.554
GPT teacher head0.659
Teacher spread0.105 · 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