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Record W4245813382 · doi:10.24124/2009/bpgub607

Rural acute care nursing in British Columbia and Alberta: An interpretive description of professionalism.

2009· dissertation· en· W4245813382 on OpenAlexafffundabout
Kelly Joan Zibrik

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsLibrary and Archives Canada
FundersGovernment of Canada
KeywordsNursingAcute careMedicineRural areaInterpretation (philosophy)Rural healthCareer PathwaysJob satisfactionHealth carePsychologyPolitical scienceMedical education

Abstract

fetched live from OpenAlex

Delivery of health care services in rural areas of Canada is challenging due to geographic and economic factors, and persistent problems with recruiting and retaining nurses. Registered Nurses in acute care represent the largest cohort of health care workers in rural Canada, and little is known about their professional experiences. The purpose of this study was to understand how rural acute care nurses in British Columbia and Alberta experience professionalism and professional practice. Eight interview transcripts from a national study entitled, The Nature of Nursing Practice in Rural and Remote Canada were analyzed using an interpretive description method. Analysis and interpretation revealed that rural nurses experience professionalism in the community and workplace contexts. Being visible and embracing reality emerged as central themes in rural nurses' experiences of professionalism. Findings from this study contribute a greater understanding of professionalism in rural nursing, and its relationship to job satisfaction, recruitment, and retention.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.967
Threshold uncertainty score0.356

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0150.009
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0010.002
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 head0.023
GPT teacher head0.425
Teacher spread0.402 · 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
Published2009
Admission routes3
Has abstractyes

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