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Record W2259161000 · doi:10.1177/2333393615607840

Advancing Telephone Focus Groups Method Through the Use of Webinar

2015· article· en· W2259161000 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

VenueGlobal Qualitative Nursing Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversity of TorontoBarrie Urology GroupPublic Health Ontario
Fundersnot available
KeywordsFocus groupFocus (optics)Public healthTelephone interviewTelephone numberMedical educationPublic relationsPsychologyMedicineComputer scienceSociologyPolitical scienceBusinessNursingMarketingSocial science

Abstract

fetched live from OpenAlex

Telephone focus groups have been increasingly popular in public health research and evaluation. One of the main concerns of telephone focus groups is the lack of nonverbal cues among participants, which could limit group interactions and dynamics during the focus group discussion. To overcome this limitation, we supplemented telephone focus groups with webinar technology in a recent evaluation of a provincial public health program in Ontario, Canada. In this article, we share the methods used and our experiences in conducting telephone focus groups supplemented with webinar technology, including advantages and challenges. Our experience will inform other researchers who may consider using telephone focus groups with webinars in future research and evaluation.

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)0.043
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.302
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.005
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.538
GPT teacher head0.638
Teacher spread0.100 · 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