MétaCan
Menu
Back to cohort
Record W2950345279 · doi:10.12927/cjnl.2019.25848

Guidance for Ethical Leadership in Nursing Codes of Ethics: An Integrative Review

2019· review· en· W2950345279 on OpenAlexaffvenue
Kara Schick‐Makaroff, Janet Storch

Bibliographic record

VenueNursing leadership · 2019
Typereview
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of VictoriaUniversity of Alberta
Fundersnot available
KeywordsNursingEthical codePsychologyMedicinePolitical sciencePublic relations

Abstract

fetched live from OpenAlex

There has been limited attention to ethical leadership for formal nurse leaders around the world. Assuming that codes of ethics provide meaningful standards of what is expected of health professionals, what specific guidance for ethical leadership is available to formal nurse leaders in national nursing codes of ethics? We conducted an integrative review of national nursing codes of ethics for 131 member countries of the International Council of Nurses (ICN). In the ICN Code, nurse managers/leaders are highlighted for their role in ethical practice. With the exception of the US, no other country code focuses as much attention on formal nurse leaders. While all country codes (except the United States) implicitly group nurses, practitioners and managers together, most codes do not provide meaningful guidance for formal nurse leaders. The level of ethical guidance provided to formal nurse leaders in national nursing codes of ethics is lacking. However, creating a separate code of ethics for formal nurse leaders is not the answer. Rather, including specific guidance in nursing codes of ethics not only informs nurses about what they can expect of nurse leaders but also allows formal nurse leaders to use the code with their own senior leaders, conveying what their professional body expects of them.

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)0.044
metaresearch head score (Gemma)0.111
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.410
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.111
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0090.059
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 head0.849
GPT teacher head0.649
Teacher spread0.200 · 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 designSystematic review
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

Citations16
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueNursing leadershipSame topicEthics in medical practiceFrench-language works237,207