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Record W3200874023 · doi:10.1177/08445621211034358

Understanding How Nursing Students Experience Becoming Relational Practitioners: A Narrative Inquiry

2021· article· en· W3200874023 on OpenAlexaffvenue
Louela Manankil‐Rankin, Jasna Schwind, Sophia Aksenchuk

Bibliographic record

VenueCanadian Journal of Nursing Research · 2021
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsToronto Metropolitan UniversityNipissing University
Fundersnot available
KeywordsNarrativeExpression (computer science)PsychologyNarrative inquiryIdentity (music)CreativityPedagogyComputer scienceSocial psychologyAesthetics

Abstract

fetched live from OpenAlex

BACKGROUND: Teaching nursing students to become relational practitioners requires theoretical approaches and strategies that engender personal and aesthetic knowing. These qualities closely parallel those that define relational practice. The use of creative self-expression in supporting the development of student capacity for relational practice offers a viable approach. PURPOSE: To learn how nursing students' engagement in creative self-expression activities may impact the construction of their professional identity and capacity for relational practice as novice nurses. METHOD: Clandinin and Connelly's narrative inquiry approach was used to explore nursing students' experiences of learning how to become relational practitioners. Four new nurse graduates engaged in a follow-up focus group using Schwind's narrative reflective process to discuss the impact of a relational practice workshop series. FINDINGS: These entailed an intentional engagement in relationships with patients, which required attention to the co-constructed relational space. The creative approaches used to facilitate students' learning informed their awareness that led to their transformation. IMPLICATIONS: Educating future nurses who are relational, person-centered practitioners requires a holistic approach to teaching/learning which also includes creative self-expression.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.467
GPT teacher head0.505
Teacher spread0.038 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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