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Record W3026378509 · doi:10.1080/22423982.2020.1766319

Perspectives of Nunavut patients and families on their cancer and end of life care experiences

2020· article· en· W3026378509 on OpenAlexafffundabout
Tracey Galloway, Sidney Horlick, Maria Cherba, Madeleine Cole, Roberta L. Woodgate, Gwen Healey Akearok

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsNOSM UniversityUniversity of ManitobaNunavut Research InstituteUniversity of TorontoQaujigiartiit Health Research CentreLaurentian University
FundersCanadian Institutes of Health Research
KeywordsReferralService providerSummative assessmentNursingHealth careService (business)End-of-life careMedicineCommunity healthConsistency (knowledge bases)Palliative carePsychologyFamily medicinePublic healthFormative assessmentPolitical scienceBusinessPedagogy

Abstract

fetched live from OpenAlex

The present study arose from a recognition among service providers that Nunavut patients and families could be better supported during their care journeys by improved understanding of people’s experiences of the health-care system. Using a summative approach to content analysis informed by the Piliriqatigiinniq Model for Community Health Research, we conducted in-depth interviews with 10 patients and family members living in Nunavut communities who experienced cancer or end of life care. Results included the following themes: difficulties associated with extensive medical travel; preference for care within the community and for family involvement in care; challenges with communication; challenges with culturally appropriate care; and the value of service providers with strong ties to the community. These themes emphasise the importance of health service capacity building in Nunavut with emphasis on Inuit language and cultural knowledge. They also underscore efforts to improve the quality and consistency of communication among health service providers working in both community and southern referral settings and between service providers and the patients and families they serve.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.004
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.352
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2020
Admission routes3
Has abstractyes

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