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Record W2589051451 · doi:10.5539/ass.v13n3p89

Economic Analysis of the Latent Factors Related to the Nursing Shortage

2017· article· en· W2589051451 on OpenAlexvenueno aff
Hend Mohumed Hani Kandiel, Sanaa Abd Elmonem Gharib

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
FundersCairo University
KeywordsCronbach's alphaEconomic shortageAuditNursingDescriptive statisticsData collectionNursing shortageWork (physics)Descriptive researchSample (material)MedicineBusinessPsychologyNurse educationSociologyAccounting

Abstract

fetched live from OpenAlex

The aim of the study was, to economically analyze o the latent factors related to nursing shortage at Cairo University Hospitals. Research design: A descriptive, methodological design was utilized. Research Questions: 1) Is the economic analysis of nursing shortage related to the actual auditing records of nursing data at Cairo University Hospitals (2011-2015). 2) What are the contributing factors leading to the nursing shortage at Cairo University Hospitals. 3) What are the economic recommendations for the present concerns related to nursing shortage. Tools of data collection: The researchers used auditing records related to nursing staff at mentioned area (2011-2015) and Questionnaire. Random sample of (N= 179). Cronbach's Alpha was 0.885. The finding revealed that nurses supply, mostly from Secondary School (84%). A critical demand for more nurses 30%-40% in certain units due to high work load. Most of the nurses were not satisfied about monitory compensation, participation in decision making and inadequate supplies.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.467
Teacher spread0.414 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

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