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Record W2137063634 · doi:10.33524/cjar.v15i3.158

Barbour, R. (2007). Doing Focus Groups. London: SAGE Publications. 174 pp. ISBN 978-0- 7619-4978-7.

2015· article· en· W2137063634 on OpenAlexaffvenue
Vivian Zenari

Bibliographic record

VenueThe Canadian Journal of Action Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsAthabasca University
Fundersnot available
KeywordsGlossaryLibrary scienceFocus groupSubject (documents)Table of contentsIndex (typography)Focus (optics)SociologyComputer sciencePhilosophyWorld Wide WebLinguistics

Abstract

fetched live from OpenAlex

Focus groups can be used to gather data for primary analysis or to identify areas of need as a preliminary step in research design. Rosaline Barbour’s Doing Focus Groups should be of interest to those considering the use of focus groups for their action research. This book is one of the eight-volume SAGE Qualitative Research Kit series edited by Uwe Flick, professor of qualitative research in social science and education at the Free University of Berlin. It has eleven chapters and includes a glossary, reference list, author index, and subject index. The book begins with broader conceptual topics (Chapter One is called “Introducing Focus Groups”) and grows more practical in later chapters, which are arranged in the order by which a research project would tend to unfold. The chapters are organized similarly. Each begins with an internal table of contents and a list of learning objectives. At the end of each chapter is a list of key ideas and supplementary readings relevant to that chapter. The book contains a generous number of illustrative examples from published research--often the Barbour’s own work in health research--to help elucidate chapter contents.

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)0.032
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.231
GPT teacher head0.453
Teacher spread0.222 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2015
Admission routes2
Has abstractyes

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