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Record W4205953036 · doi:10.12927/cjnl.2021.26680

Commentary – Dear Federal Chief Nursing Officer: Why Canada Needs You

2021· article· en· W4205953036 on OpenAlexvenueaboutno aff
Angela Wignall

Bibliographic record

VenueNursing leadership · 2021
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerPoliticsContext (archaeology)NursingPolitical scienceNurse educationState (computer science)Public relationsPublic administrationMedicineLawGeography

Abstract

fetched live from OpenAlex

Calls for national-level chief nursing officers are over a century old. However, global uptake of these roles and Canadian opportunities for nurses to lead in federal health policy environments have been limited. The absence of such a role in Canada limits connection to global activities, reduces Canadian capacity to participate as a member state in World Health Organization-led nursing activities and, within our borders, leaves the healthcare system without national leadership to coordinate and liaise with senior nurses across our provinces and territories for the benefit of our citizens and systems. In this article, a brief history of global advocacy for state or national level chief nursing officer roles and examples of federal chief nursing officers, in the Canadian context, offers a consideration of the unique contribution of nursing knowledge and leadership to health policy - extending arguments for nursing leadership in the policy arena beyond traditional arguments of strength in numbers or unique claims to caring. Findings from a Canadian national project by the Global Nursing Leadership Institute further illuminate the concrete steps we need to take toward enabling full-spectrum nursing leadership in policy, where policy science, political competency, identification of policy nurses and a revitalization of organizational structures across the country can extend the vision for nursing leadership in policy beyond a single seat at a single table.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.077
GPT teacher head0.299
Teacher spread0.221 · 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 designNot applicable
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

Citations3
Published2021
Admission routes2
Has abstractyes

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