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Record W2320337890 · doi:10.1080/10376178.2016.1171728

Experience and representations of health and social services in a community of Nunavik

2015· article· en· W2320337890 on OpenAlexaffabout
Sarah Fraser, Lucie Nadeau

Bibliographic record

VenueContemporary Nurse · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMcGill UniversityCentre de Santé et de Services Sociaux de la MontagneUniversité de MontréalCégep Marie-Victorin
FundersSocial Science Research Council
KeywordsThematic analysisFeelingPsychosocialPerceptionQualitative researchPsychologyNursingHealth carePublic relationsMedicineSociologySocial psychologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: The study aims to explore representations and experiences with health and social services in an Inuit community of Nunavik. METHODS: A total of 15 semi-structured interviews were conducted with Inuit adults from a community of Northern Quebec. Informal interviews and participatory observation was conducted on six visits over two years. A thematic inductive analysis of data was conducted. RESULTS: Participants' experiences with care were largely related to the nature of interactions with service providers, and feelings about whether perceived needs were being met. Often these needs were socio-economic. Perceptions of services were based on concepts of trust, privacy and fear of consequences of divulging information, three intrinsically related themes. CONCLUSIONS: Reflections must be made on how to address the socio-economic needs of patients and how to go beyond the immediate requests to hear the psychosocial needs that patients might not feel safe to talk about.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.242
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.009
Scholarly communication0.0030.001
Open science0.0010.004
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 head0.076
GPT teacher head0.394
Teacher spread0.318 · 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

Citations33
Published2015
Admission routes2
Has abstractyes

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