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Record W2989865215 · doi:10.1080/21635781.2019.1689875

The Validation of the Military and Veteran Family Cultural Competency Model (MVF-CCM)

2019· article· en· W2989865215 on OpenAlexaff
Linna Tam‐Seto, Terry Krupa, Heather Stuart, Patricia Lingley‐Pottie, Alice Aiken, Heidi Cramm

Bibliographic record

VenueMilitary Behavioral Health · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsDalhousie UniversityQueen's University
Fundersnot available
KeywordsCLARITYFocus groupPsychologyMedical educationCultural competenceResource (disambiguation)Qualitative propertyHealth careNursingApplied psychologyMedicinePedagogySociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

There is increasing use of cultural competency models to guide health care interactions with military community members, including families, however, at this time there is no validated model. This study confirms the accuracy of the Military and Veteran Family Cultural Competency Model (MVF-CCM). Using a systems theory-informed qualitative approach, focus groups and interviews were conducted. Data were analyzed using a step-wise process to integrate changes. Feedback was provided to both the model and framework to expand on content and increase clarity. The MVF-CCM is an evidence-informed resource to support the development of cultural competent health care curriculum, continuing education opportunities, and clinical practice.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.063
GPT teacher head0.376
Teacher spread0.312 · 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 teacher head, not a consensus.

Study designObservational
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

Citations11
Published2019
Admission routes1
Has abstractyes

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