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Record W3138785831 · doi:10.3390/ijerph18073411

Understanding the Environment for Health-Promoting Schools Policies in Nova Scotia: A Comprehensive Scan at the Provincial and Regional School Level

2021· review· en· W3138785831 on OpenAlexafffundabout
Anna DeMello, Joshua Yusuf, Margaret Kay-Arora, Camille L. Hancock Friesen, Sara Kirk

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typereview
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsDalhousie University
FundersDepartment of Health, Western Cape GovernmentPublic Health AgencyPublic Health Agency of Canada
KeywordsNova scotiaNova (rocket)Political scienceEnvironmental healthMedical educationGeographyRegional scienceMedicineEngineeringArchaeologyAeronautics

Abstract

fetched live from OpenAlex

The World Health Organization has identified the school community as a key setting for health promotion efforts, laying out its priorities in the Health-Promoting Schools (HPS) framework. This framework offers a comprehensive approach that has been adopted in countries around the globe, with defining characteristics focused around the school curriculum and environment. Nova Scotia (NS) adopted the HPS framework at a provincial level in 2005, but it has been variably implemented. We aimed to identify, categorize, and broadly describe the environment for HPS policies in NS. Four iterative steps were employed: (1) a scan of government and regional school websites to identify publicly available policies; (2) consultations with provincial departments with respect to policy relevance and scope; (3) cross-comparison of policies by two reviewers; (4) compilation of policies into an online database. Seventy policies at the provincial level and 509 policies across eight public school regions were identified. Policies focusing on a 'safe school environment' were most common; those addressing mental health and well-being, physical activity, nutrition and healthy eating, and substance use were among those least commonly identified. This scan provides a comprehensive overview of HPS-relevant policies in NS, along with relative proportions and growth over time. Our findings suggest areas of policy action and inaction that may help or hinder the implementation of HPS principles and values.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.591
GPT teacher head0.564
Teacher spread0.027 · 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
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

Citations10
Published2021
Admission routes3
Has abstractyes

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