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Linking Learners for Life Where They Live (L4): Developing a Global Health Initiative for Student Engagement

2015· article· en· W2078682718 on OpenAlexafffundabout
Maxine Watt, Lorna Butler, Heather Exner-Pirot, Amy Wright

Bibliographic record

VenueJournal of Professional Nursing · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMcMaster UniversityUniversity of Saskatchewan
FundersUniversidad de la República UruguayPublic Health Agency of CanadaUniversity of Saskatchewan
KeywordsCircumpolar starGeneral partnershipContext (archaeology)IndigenousCommunity engagementMedical educationStudent engagementSociologyPedagogyPublic relationsPolitical scienceMedicineGeography

Abstract

fetched live from OpenAlex

This article describes a graduate student learning experience as part of an international nursing collaborative working together to develop an academic partnership for global health education in the circumpolar north. The experience provided an opportunity to conduct a pilot project in a rural, remote, northern community using an indigenous, global context. Building on the Canadian-Siberian collaboration, the graduate student attended an academic institution in Siberia, where she focused on the sharing of expertise, knowledge, and insights in order to address the challenges facing indigenous people in achieving optimal health and well-being in the circumpolar north. The goal was to create a foundation for "putting health into place" in a northern context, with the hope of creating shared learning opportunities for undergraduate students between the 2 countries.The intent is to share the approach used by the graduate student to use a conceptual model to assess the feasibility of creating a context-relevant global health experience for northern nursing education.

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)0.007
metaresearch head score (Gemma)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.220
GPT teacher head0.564
Teacher spread0.343 · 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

Citations5
Published2015
Admission routes3
Has abstractyes

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