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A conceptual framework contributing to nursing administration and research

2007· review· en· W2117957904 on OpenAlexafffund
Alain Biron, Marie‐Claire Richer, Hélène Ezer

Bibliographic record

VenueJournal of Nursing Management · 2007
Typereview
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcGill University
FundersMcGill University Health CentreCanadian Health Services Research Foundation
KeywordsHealth careNursingContext (archaeology)Nursing researchNursing careAdministration (probate law)Team nursingNursing shortageMedicineNursing managementNurse educationPolitical science

Abstract

fetched live from OpenAlex

The health care system has undergone major changes in the last decade. With greater acuity and complexity of illness, the adoption of innovative technologies and the shortage of health care personnel, the coordination and integration of health care services has become increasingly demanding for administrators. Growing dissatisfaction and concerns about safety issues are being expressed by the users of care who need to navigate through an increasingly complex system and by health care personnel who feel less efficient within the organization. Nursing administrators have a responsibility to address these issues but there is little scientific evidence to guide their actions. There are also few comprehensive models highlighting the main components of nursing administration - models that could guide nursing administration research. This paper presents a conceptual framework for nursing administration and research that links patient health care needs, nursing resources and the nursing care processes to the context of the health care system, and the social, political and cultural environments of care. A selected review of the oncology and cancer care literature is presented to demonstrate how this framework can organize existing knowledge about these concepts in the context of cancer care.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.516
GPT teacher head0.623
Teacher spread0.107 · 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 designOther design
Domainnot available
GenreReview

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

Citations21
Published2007
Admission routes2
Has abstractyes

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