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Record W3033320438 · doi:10.1177/0844562120928794

Charting a Research Agenda for the Advancement of Nursing Organizations’ Influence on Health Systems and Policy

2020· article· en· W3033320438 on OpenAlexaffvenueabout
Patrick Chiu, Susan Duncan, Nora Whyte

Bibliographic record

VenueCanadian Journal of Nursing Research · 2020
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsUniversity of British ColumbiaUniversity of VictoriaUniversity of Alberta
Fundersnot available
KeywordsManagement scienceEngineering ethicsPolitical scienceSociologyEngineering

Abstract

fetched live from OpenAlex

Nursing organizations across Canada play a significant role in influencing and shaping public policy. 2020, the Year of the Nurse and the Midwife, is an opportune time not only to support nurses in building policy leadership but also to explore opportunities to better understand and strengthen the policy advocacy work of nursing organizations. Given various social, political, and economic forces, the nature of organized nursing across Canada is changing significantly. We draw on recent key national and global events including our systematic inquiry into Canada's 2019 federal election, the Year of the Nurse and Midwife, and the Coronavirus pandemic to examine how Canadian nursing organizations respond in highly complex and evolving contexts. We use our observations to offer a vision and chart a research agenda for the advancement of nursing organizations' influence on health systems and policy. Specifically, we focus on three key areas including examining nursing organizations' policy agendas and spheres of influence; nursing organizations' decision-making around policy advocacy tactics and engagement approaches; and the impact of policy advocacy coalitions and networks on nursing organizations' influence.

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)0.006
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
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 head0.299
GPT teacher head0.520
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 designQualitative
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

Citations14
Published2020
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Nursing ResearchSame topicNursing Education, Practice, and LeadershipFrench-language works237,207