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Record W2143859244 · doi:10.1177/1049732304272015

Qualitative Teamwork Issues and Strategies: Coordination Through Mutual Adjustment

2005· article· en· W2143859244 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

VenueQualitative Health Research · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTeamworkReciprocity (cultural anthropology)ReflexivityQualitative researchMultidisciplinary approachGrounded theoryPsychologyProcess (computing)Focus groupKnowledge managementManagement scienceSociologySocial psychologyComputer sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

Multidisciplinary research teams that include faculty, students, and volunteers can be challenging and enriching for all participants. Although such teams are becoming commonplace, minimal guidance is available about strategies to enhance team effectiveness. In this article, the authors highlight strategies to guide qualitative teamwork through coordination of team members and tasks based on mutual adjustment. Using a grounded theory exemplar, they focus on issues of (a) building the team, (b) developing reflexivity and theoretical sensitivity, (c) tackling analytic and methodological procedures, and (d) developing dissemination guidelines. Sharing information, articulating project goals and elements, acknowledging variation in individual goals, and engaging in reciprocity and respectful collaboration are key elements of mutual adjustment. The authors summarize conclusions about the costs and benefits of 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)0.064
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.721
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0640.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.688
GPT teacher head0.753
Teacher spread0.065 · 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