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Record W3159378291 · doi:10.1111/nin.12420

Being and becoming a nurse: Toward an ontological and reflexive turn in first‐year nursing education

2021· article· en· W3159378291 on OpenAlexaff
Karen Jenkins, Elizabeth Anne Kinsella, Sandra DeLuca

Bibliographic record

VenueNursing Inquiry · 2021
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsLondon Health Sciences CentreMcGill University Health CentreFanshawe CollegeWestern University
Fundersnot available
KeywordsReflexivityDialogicNurse educationNursingValue (mathematics)IdeologyNursing researchSociologyMedicinePedagogyPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

In this paper, we call for an ontological and reflexive turn in first-year nursing education. An ontological turn focuses on formation, the 'being' and 'becoming' of a nurse, and emphasizes the value of nursing knowledge. First-year nursing students often possess romanticized ideals about being a nurse that devalues the knowledge and expertise of nurses. We posit a thoughtful ontological orientation within nursing education that shifts the emphasis toward becoming skillful nurses, with expertise grounded in nursing perspectives. A focus on formation includes discussions regarding ideologies, dominant perspectives, and reflexive explorations of students' views of nursing juxtaposed with the realities of nursing practice. We propose ontologic reflexivity as an approach to consider what perspectives are prioritized (or not) within the nursing classroom. Within pedagogical dialogic spaces, ontologic reflexivity calls on educators to create opportunities for students to learn the value of nursing knowledge along with other forms of knowledge. We consider ways in which an ontological and reflexive turn within the first year of nursing education may contribute to the formation of nursing students who value nursing knowledge, are open-minded to various forms of knowledge, and possess an intentional reflexive way of being.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.106
GPT teacher head0.508
Teacher spread0.403 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2021
Admission routes1
Has abstractyes

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