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Record W2270167238 · doi:10.1177/1609406915621402

Learning to Listen

2015· article· en· W2270167238 on OpenAlexaff
Sanja Petrovic, Daphne Lordly, Susan M. Brigham, Mary Delaney

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsActive listeningPsychologyQualitative researchReflection (computer programming)PedagogyThe artsMathematics educationMedical educationVisual artsComputer scienceSociologyMedicineCommunicationArt

Abstract

fetched live from OpenAlex

The Listening Guide (LG) is a relational, voice-centered method to analyzing qualitative research data. This article provides an account of how the LG was modified for a study that examined personal critical reflection papers written by 27 fourth-year dietetics university students after they participated in an arts-informed module on body image in a dietetics professional practice course. By relying on the main principles of the LG, we demonstrate how the LG can help us to listen and hear previously unnoticed and underappreciated voices. The purpose of this article is to serve as a source of guidance and support for researchers looking to implement the LG method beyond its original purpose, which was for transcribed interviews.

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)0.124
metaresearch head score (Gemma)0.101
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.420
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1240.101
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.892
GPT teacher head0.784
Teacher spread0.109 · 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 designQualitative
Domainnot available
GenreMethods

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

Citations27
Published2015
Admission routes1
Has abstractyes

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