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Record W2491741224 · doi:10.1177/1609406916659292

Narrative Research Evolving

2016· article· en· W2491741224 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

VenueInternational Journal of Qualitative Methods · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of AlbertaIsland HealthUniversity of Victoria
Fundersnot available
KeywordsNarrativeFlourishingNarrative inquiryEpistemologyQualitative researchNarrative networkSociologyNarrative criticismEngineering ethicsPsychologySocial scienceSocial psychologyEngineeringPhilosophy

Abstract

fetched live from OpenAlex

Narrative research methodology is evolving, and we contend that the notion of emergent design is vital if narrative inquiry (NI) is to continue flourishing in generating new knowledge. We situate the discussion within the narrative turn in qualitative research while drawing on experiences of conducting a longitudinal narrative study. The philosophical tensions encountered are described, as our understanding and application of narrative approaches evolved. We outline challenges in data collection and analysis in response to what we were learning and identify institutional barriers within ethics review processes that potentially impede emergent approaches. We conclude that researchers using NI can, and must, pursue unanticipated methodological changes when in the midst of conducting the inquiry. Understanding the benefits and institutional barriers to emergent aspects of design is discussed in this ever-maturing approach to qualitative research.

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)0.162
metaresearch head score (Gemma)0.136
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.458
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1620.136
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.981
GPT teacher head0.868
Teacher spread0.113 · 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