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Record W357427481

Aboriginal nurses: Insights from a national study

2006· article· en· W357427481 on OpenAlexfundaboutno aff
Judith C. Kulig, Norma J. Stewart, Debra Morgan, Mary E. Andrews, Martha MacLeod, Roger Pitblado

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleOntario Ministry of Health and Long-Term CareNova Scotia Health Research FoundationGovernment of NunavutCanadian Health Services Research FoundationMichael Smith Health Research BCUniversity of Northern British Columbia
KeywordsPsychologyNursingPublic relationsMedicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Aboriginal registered nurses have been identified as an essential group in the delivery of health services in First Nations communities. Despite this, there is a lack of information about this group of nurses
\nin Canada. This article presents information about this group taken from two components of a national study, The Nature of Nursing
\nPractice In Rural and Remote Canada: documentary analysis and a national survey of nurses. The Aboriginal nurse participants were predominantly female, between the ages of 40 and 49, diploma prepared and with licensure for less than 10 years. The survey data showed 41.4 per cent returned to their home communities to work. The participants
\nnoted how they enjoyed the challenges of rural and remote nursing and wanted to raise their families in these small communities.
\nThey have been able to create supportive work environments, particularly with their nursing colleagues. The nurses are committed to working in rural and remote communities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.049
GPT teacher head0.417
Teacher spread0.368 · 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; both teacher heads agree on what is shown here.

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

Citations9
Published2006
Admission routes2
Has abstractyes

Explore more

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