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Record W1994128089 · doi:10.5737/1181912x2314452

Core areas of practice and associated competencies for nurses working as professional cancer navigators

2013· article· en· W1994128089 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsCancer Care Nova Scotia
FundersCanadian Institutes of Health Research
KeywordsCore competencyEmpowermentNursingMedicineProfessional developmentPsychologyMedical educationBusiness

Abstract

fetched live from OpenAlex

UNLABELLED: Fillion et al. (2012) recently designed a conceptual framework for professional cancer navigators describing key functions of professional cancer navigation. PURPOSE: Building on this framework, this study defines the core areas of practice and associated competencies for professional cancer navigators. METHODS: The methods used in this study included: literature review, mapping of navigation functions against practice standards and competencies, and validation of this mapping process with professional navigators, their managers and nursing experts and comparison of roles in similar navigation programs. FINDINGS: Associated competencies were linked to the three identified core areas of practice, which are: 1) providing information and education, 2) providing emotional and supportive care, and 3) facilitating coordination and continuity of care. CONCLUSION: Cancer navigators are in a key position to improve patient and family empowerment and continuity of care. IMPLICATIONS: This is an important step for advancing the role of oncology nurses in navigator positions and identifying areas for further research.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.104
GPT teacher head0.428
Teacher spread0.324 · 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