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Record W2785745330 · doi:10.12927/cjnl.2018.25382

Nurses Taking the Lead: A Community Engagement and Knowledge Exchange Forum on Substance Abuse and Addiction in Prince Albert, Saskatchewan

2017· article· en· W2785745330 on OpenAlexafffundvenueabout
Geoffrey Maina, Brenda Mishak, Anthony de Padua, Gillian Strudwick, Angelica Docabo, Hira Tahir

Bibliographic record

VenueNursing leadership · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsCentre for Addiction and Mental HealthPrince Albert Grand Council
FundersCanadian Institutes of Health ResearchCollege of Nursing, University of SaskatchewanUniversity of Saskatchewan
KeywordsAddictionSubstance abuseSubstance usePsychologyNursingPublic relationsPolitical sciencePsychiatryMedicine

Abstract

fetched live from OpenAlex

Prince Albert, Saskatchewan, is experiencing a substance use and addiction crisis with devastating consequences. To engage local stakeholders on substance use and addiction issues, nurse researchers at the University of Saskatchewan, Prince Albert Campus, planned and organized a one-day community engagement and knowledge exchange forum. The forum provided the opportunity for interested community groups, members and individuals to share their experiences and to explore novel ways to prevent and respond to the substance abuse and addiction challenges in the region. Participants included community leaders, people and families living with addiction, service providers, local stakeholders, health professionals, researchers and Indigenous Elders. This paper describes the process and outcomes of this event and describes the role of nurse scholars in leading these efforts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.252
GPT teacher head0.347
Teacher spread0.095 · 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

Citations8
Published2017
Admission routes4
Has abstractyes

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