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Record W4226486887 · doi:10.7748/nr.2022.e1828

Perspectives on reporting non-verbal interactions from the contemporary research focus group

2022· article· en· W4226486887 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNurse Researcher · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsFocus groupFocus (optics)ModerationPsychologyQualitative researchGroup (periodic table)Social psychologySynchronicitySociologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: The main defining attribute that delineates focus groups from other methods of collecting data is that data are generated through participants communicating with each other rather than solely with the group moderator. The way in which interactions take place across group interviews and focus groups varies, yet both are referred to as focus groups, resulting in a broad umbrella term for its numerous manifestations. AIM: To reflect on how focus groups are adopted and reported, including the use of the term 'focus group'. DISCUSSION: The authors recognise that the term 'focus group' is sometimes used synonymously with 'group interview' but argue that this practice must be challenged. They suggest using terms that indicate the type of space and synchronicity of the focus group, prefixed with 'in-person' or 'conventional' to identify traditional focus groups. They also suggest separating virtual group interviews into 'synchronous' and 'asynchronous', based on whether the participants and researchers can engage with each other in real time. CONCLUSION: There is a need for qualitative researchers to reach a consensus about the nature of focus groups and group interviews, as well as where their differences and similarities lie. IMPLICATIONS FOR PRACTICE: The authors hope to encourage nurse researchers to think about these issues when labelling, planning, analysing and reporting studies involving focus groups.

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)0.032
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.461
GPT teacher head0.578
Teacher spread0.117 · 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