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Record W2209591481

An Appreciative Inquiry into the Healthcare Concerns of the Elder Hmong Women Living in Alaska, USA

2014· article· en· W2209591481 on OpenAlexvenueno aff
Pang Houa Lor, Babu George

Bibliographic record

VenueJournal of rural and community development · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsnot available
Fundersnot available
KeywordsIgnoranceFocus groupFunctional illiteracyAppreciative inquiryHealth carePovertySituatedSociologyPublic relationsHealthcare systemNursingGender studiesEconomic growthPolitical sciencePedagogyMedicine
DOInot available

Abstract

fetched live from OpenAlex

In addition to high levels of poverty and ignorance of the structure and conduct of the healthcare system, language and cultural barriers hamper efforts by Hmong women in the US to meet their healthcare needs. To better understand the complex interconnections among these factors, the researchers conducted a number of focus group interviews. The focus group interviews were conducted in the spirit of appreciative inquiry and resulted in thick and situated knowledge about some of the major healthcare issues faced by female members of the Hmong community. Certain methods to cope with the barriers have already organically evolved within the community framework. While highlighting and appreciating such developments, the researchers also propose alternatives to ensure that the community gets the best out of the national healthcare system. Keywords: Illiteracy, communication difficulties, cultural isolation, healthcare quality, Hmong, Alaska

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)0.003
metaresearch head score (Gemma)0.004
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 score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.054
GPT teacher head0.352
Teacher spread0.298 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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