MétaCan
Menu
Back to cohort
Record W130478199

Organizational cultural competence in community health and social service organizations: how to conduct a self-assessment.

2009· article· en· W130478199 on OpenAlexaffabout
Marcela Olavarria, Julie Beaulac, Alexandre Bélanger, Marta Y. Young, Tim Aubry

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCultural competencePublic relationsHuman servicesCompetence (human resources)SociologyPsychologyPolitical scienceSocial psychologyPedagogy
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: In an effort to address the significant socio-cultural changes in the population demographics of the United States (US) and Canada, organizations are increasingly seeking ways of improving their level of cultural competence. Evaluating organizational cultural competence is essential to address the needs of ethnic and cultural minorities. Yet, research related to organizational cultural competence is relatively new. The purpose of this paper is to review the extant literature with a specific focus on: (1) identifying the key standards that define culturally competent community health and social service organizations; and (2) outlining the core elements for evaluating cultural competence in a health and social service organization. Furthermore, issues related to choosing self-assessment tools and conducting an evaluation will be explored.

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)0.080
metaresearch head score (Gemma)0.181
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: Methods · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.424

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0800.181
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.002
Science and technology studies0.0020.003
Scholarly communication0.0040.007
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.347
Teacher spread0.289 · 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
GenreMethods

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

Citations20
Published2009
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicCultural Competency in Health CareFrench-language works237,207