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Record W2592250917 · doi:10.1108/qrj-12-2016-0073

The role of triangulation in sensitive art-based research with children

2017· article· en· W2592250917 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 Research Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTriangulationOriginalityParticipant observationNarrativePopularityQualitative researchMeaning (existential)Data collectionValue (mathematics)Diversity (politics)PsychologyQualitative propertyNarrative inquiryProject commissioningSociologyPublishingSocial psychologyComputer scienceSocial scienceMathematicsPolitical science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to highlight the critical role of triangulation to create authentic analytical frameworks amidst contradictory participant narratives in sensitive art-based research (ABR) with children. Design/methodology/approach Multiple qualitative case study research included three months of participant observation, individual semi-structured teacher interviews and open-ended art-based interviews using the Draw-Write-Narrate method (Ogina and Nieuwenhuis, 2010) with upper primary students in two schools in Kirinyaga County, Kenya. Findings The art-based approach to student interviews, combined with participant observation and teacher interviews, provided a child-centred process that illuminated students’ understandings and experiences while minimizing risks to participants. Its application requires researchers to recognize data collection and analysis as subjective processes that strongly benefit from triangulation to interpret a diversity of perspectives that may not easily align. Originality/value As ABR with children increases in popularity, it is important to identify challenges in the process of analysis and meaning-making. This paper identifies triangulation as a valuable tool for handling the challenge of diverse perspectives from child participants, particularly in conducting sensitive research that may increase the likelihood of contradictory narratives.

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)0.219
metaresearch head score (Gemma)0.074
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2190.074
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.879
GPT teacher head0.787
Teacher spread0.092 · 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