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Record W4394008894 · doi:10.3928/01484834-20240207-02

Environmental Sustainability and Climate Change Content in Canadian Baccalaureate Nursing Programs

2024· article· en· W4394008894 on OpenAlexaboutno aff
Jennifer Stephens, Kathleen Leslie

Bibliographic record

VenueJournal of Nursing Education · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorCurriculumThematic analysisSustainabilityClimate changeNurse educationMedical educationNursingPolitical sciencePsychologyMedicineSociologyPedagogyQualitative research

Abstract

fetched live from OpenAlex

Background: This study analyzed publicly available resources related to environmental and climate change material available within the Canadian Bachelor of Nursing Program curricula. Method: This thematic review project contained two stages of data collection: (1) a comprehensive team-based review of Internet materials and (2) a digital survey of program faculties. Results: Most content reviewed included references to climate change. According to survey responses from program directors ( n = 12), barriers to integrating climate change content included lack of institutional support, the perception that content was not important in undergraduate curriculum, a conviction that the material would be more appropriate for public health, and an overall lack of understanding of the topic by course authors. Conclusion: With increasing emphasis on the importance of geopolitical health and climate change to many facets of nursing practice, nurse educators require support from colleagues and postsecondary institutions to incorporate this material into undergraduate nursing curricula. [ J Nurs Educ . 2024;63(4):212–217.]

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.091
GPT teacher head0.372
Teacher spread0.282 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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