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Record W4225605582 · doi:10.1177/16094069221081594

Critical Narrative Inquiry: An Examination of a Methodological Approach

2022· article· en· W4225605582 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 · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsWestern University
Fundersnot available
KeywordsReflexivityNarrativeEpistemologyStorytellingNarrative inquiryMeaning (existential)Perspective (graphical)TemporalitySet (abstract data type)SociologyScope (computer science)Narrative criticismQualitative researchPsychologySocial scienceLinguisticsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

While stories are a central focus in narrative inquiry to examine phenomena, storytelling deconstruct values, assumptions, and beliefs to challenge taken-for-granted meanings. The objective of this paper is to examine storytelling from the perspective of knowledge paradigms, methodology, quality criteria, and reflexivity. By recognizing the elements of stories sociality, temporality, and place, the scope of a qualitative narrative study is framed where factors are expressed, shaped, and enacted. Considerations of these elements can be linked with the critical paradigm and self-reflexivity for representing and designing narrative inquiry grounded in a set of ontological and epistemological assumptions. A significant contribution of this paper is to address a methodological approach in the form of narrative inquiry to better understand the meaning of stories as rooted expressions of participants’ lived experiences. The implications of this study are to bring critical lens to worldviews that would better inform policy.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.068
metaresearch head score (Gemma)0.020
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: Methods
Teacher disagreement score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0680.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.921
GPT teacher head0.776
Teacher spread0.145 · 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