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Record W4320016679 · doi:10.18584/iipj.2022.13.3.14030

Importance of Culture in Alcohol Care

2022· article· en· W4320016679 on OpenAlexvenueno aff
Gemma Purcell‐Khodr, Emma Webster, K.G. Harrison, Angela Dawson, Katherine M. Conigrave

Bibliographic record

VenueInternational Indigenous Policy Journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
FundersNational Health and Medical Research Council
KeywordsIndigenousInterpersonal communicationNursingGrounded theoryCulturally appropriateHealth carePrimary careSociologyService providerService (business)PsychologyPublic relationsQualitative researchMedicinePolitical scienceGerontologySocial psychologyFamily medicineSocial scienceBusiness

Abstract

fetched live from OpenAlex

Integration of cultural knowledges and healing practices with Western medical approaches to alcohol care has been reported for residential and community settings. However, there is little evidence on how culture features in alcohol care in primary health settings. We analysed data from semi-structured interviews (from a broader study) with 17 First Nations Australian staff (n=8 men, n=9 women) from 11 Aboriginal and Torres Strait Islander Community Controlled Health Services. We used grounded theory and the 8-ways Aboriginal pedagogy in analysis. We describe three key themes: 1) interpersonal processes; 2) a both-ways approach to healing and alcohol care; and 3) service-wide strategies to achieving both-ways healing. We discuss policy implications of facilitating bicultural alcohol care in primary health settings.

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)0.011
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0100.028
Scholarly communication0.0120.005
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.480
Teacher spread0.412 · 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 designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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