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Record W7042543868

The Perspectives of Canadian Nurse Entrepreneurs and Related Policy Implications: An Interpretive Description Study

2017· article· en· W7042543868 on OpenAlexaffabout

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsHealth careEntrepreneurshipNurse educationQualitative researchNursing practiceNursing researchHealth policyResistance (ecology)Service (business)
DOInot available

Abstract

fetched live from OpenAlex

Nursing entrepreneurship presents as a viable and innovative approach for nursing practice while contributing to health system transformation. And yet, in countries such as Canada where universal health care funding has most nurses working as employees for state-funded health service providers, few nurses are self-employed. This qualitative study acquired the perspectives of eleven practicing Canadian nurse entrepreneurs from across Canada, and six Canadian nurse leaders with respect to current nursing practice, contexts, and issues that serve to inform and guide the development of national and provincial/territorial policies that support nursing entrepreneurship. Three categorical themes were identified: Going alone versus going along; Resistance outside of convention; and, Nursing entrepreneurship: Outcomes and opportunities. The overall findings highlight a resistance-resilience dialectic for nurse entrepreneurs, the outcome of which sees them advancing nursing practice and health system reform. Meso and macro level policy recommendations that aim to support nursing enterprise within Canada are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.095
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0470.013
Scholarly communication0.0110.003
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.324
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes2
Has abstractyes

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