MétaCan
Menu
Back to cohort
Record W3011852104 · doi:10.1177/1355819620911679

Exploring the role of lay and professional patient navigators in Canada

2020· article· en· W3011852104 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Health Services Research & Policy · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsHealth Sciences CentreUniversity of New Brunswick
Fundersnot available
KeywordsThematic analysisContext (archaeology)Qualitative researchNursingWork (physics)PsychologyMedicineMedical educationSociologyGeography

Abstract

fetched live from OpenAlex

OBJECTIVES: To explore the roles of patient navigators in different settings and situations for various patient populations and to understand the rationale for implementing lay and professional models of patient navigation in a Canadian context. METHODS: A qualitative descriptive design was applied, using interviews with 10 patient navigators from eight Canadian provinces, and Braun and Clarke's six phases of thematic analysis to guide the analysis of interview transcripts. RESULTS: Findings indicate that a patient navigator's personality and experience (personal and work-related) may be more important than their specific designation (i.e. lay or professional). CONCLUSIONS: Lay and professional navigators in Canada appear to be well suited to provide navigational services across populations. This study has the potential to inform future research, policy, and the delivery of navigation programmes in Canada.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.184
GPT teacher head0.505
Teacher spread0.321 · 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