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Record W2803069996 · doi:10.5430/jnep.v8n9p113

Getting to the root of it: How do faculty address professional boundaries, role expansion, and intra-professional collaboration?

2018· article· en· W2803069996 on OpenAlexaffvenueabout
Jacqueline Limoges, Kim Jagos, Sara Lankshear, Sandy Madorin, Deb Witmer

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsGeorgian College
Fundersnot available
KeywordsCLARITYLegitimacyQualitative researchNursingNurse educationPower (physics)Professional developmentMedical educationPedagogyPsychologySociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

Background: Little research exists to guide nursing faculty to respond to the most recent entry-to-practice education changes and subsequent practice and knowledge expansion for nurses. The purpose of this study was to explore the experiences of faculty as they teach about professional boundaries and role clarity to college and university nursing students and how this teaching is connected to in intra-professional collaboration.Methods: This qualitative research study used a critical feminist sociology to analyze interviews and relevant documents. Twenty-five nursing faculty from an Ontario, Canada school were interviewed.Results: Through our analysis we detected two main findings. The first was the activation of hierarchies positioning the university program with more status and legitimacy than the college program, and how this established power relations and impeded nursing education for role clarity. The second was the struggle to articulate the actual differences between the roles and contributions of the Registered Practical Nurse (RPN) and the Registered Nurse (RN) and how this struggle impeded education for effective collaboration and role clarity.Conclusions: Supporting faculty to recognize the distinct and overlapping contributions of each type of nurse can support educational reform that promotes competencies in collaborative care.

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.002
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 head0.058
GPT teacher head0.432
Teacher spread0.374 · 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 designNot applicable
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
Published2018
Admission routes3
Has abstractyes

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