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Record W2808288153 · doi:10.1111/nin.12249

Once upon a time: Storytelling as a knowledge translation strategy for qualitative researchers

2018· article· en· W2808288153 on OpenAlexafffund
Anne Bourbonnais, Cécile Michaud

Bibliographic record

VenueNursing Inquiry · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsUniversité de SherbrookeUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
FundersFonds de Recherche du Québec - SantéRéseau de recherche portant sur les interventions en sciences infirmières du Québec
KeywordsStorytellingQualitative researchKnowledge translationContext (archaeology)PragmatismMeaning (existential)ModalitiesPsychologyComputer scienceSociologyEpistemologyKnowledge managementLinguisticsNarrative

Abstract

fetched live from OpenAlex

Qualitative research should strive for knowledge translation toward the goal of closing the gap between knowledge and practice. However, it is often a challenge in nursing to identify knowledge translation strategies able to illustrate the usefulness of qualitative results in any given context. This article defines storytelling and uses pragmatism to examine storytelling as a strategy to promote the knowledge translation of qualitative results. Pragmatism posits that usefulness is defined by the people affected by the problem and that usefulness is promoted by modalities, like storytelling, that increase sensitivity to an experience. Indeed, stories have the power to give meaning to human behaviors and to trigger emotions, and in doing so bring many advantages. For example, by contextualizing research results and appealing to both the reason and the emotions of audiences, storytelling can help us grasp the usefulness of these research results. Various strategies exist to create stories that will produce an emotional experience capable of influencing readers' or listeners' actions. To illustrate the potential of storytelling as a knowledge translation strategy in health care, we will use our story of discovering this strategy during a qualitative study in a nursing home as an example.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.558
GPT teacher head0.596
Teacher spread0.039 · 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; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations30
Published2018
Admission routes2
Has abstractyes

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