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Record W2033017066 · doi:10.12927/cjnl.2013.23251

Factors That Influence Career Decisions in Canada’s Nurses

2013· article· en· W2033017066 on OpenAlexafffundvenueabout
Sheri Price, Linda M. Hall, Michelle Lalonde, Gavin J. Andrews, Alexandra Harris, Sandra MacDonald‐Rencz

Bibliographic record

VenueNursing leadership · 2013
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of TorontoMcMaster UniversitySt. Lawrence CollegeCentre for Disability Prevention and RehabilitationDalhousie University
FundersHealth CanadaCanadian Foundation for Healthcare Improvement
KeywordsSocializationNursingPerceptionWork (physics)PsychologyCareer developmentJob satisfactionMedicineSocial psychology

Abstract

fetched live from OpenAlex

Understanding the experiences of nurses who have moved between the provinces and territories (P/T) in Canada for work provides insight into the role of professional socialization in career decision-making. This paper analyzes some of the qualitative data arising from a survey of nurses from across Canada. The findings provide insight into nurses' professional socialization and demonstrate that early perceptions and expectations of nursing practice can influence future career decisions such as mobility and intent to remain. Participants described how "caring" and direct patient contact were central to their choice of nursing and career satisfaction. As the data reveal, nursing is also regarded as a career that enables mobility to accommodate both family considerations and professional development opportunities. The findings highlight the need for professional socialization strategies and supports that motivate Canadian nurses to continue practising within the profession and the country.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.375
GPT teacher head0.424
Teacher spread0.049 · 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 designObservational
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

Citations8
Published2013
Admission routes4
Has abstractyes

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