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Record W1987170937 · doi:10.4236/sm.2013.32019

Adapting Communities That Care in Urban Aboriginal Communities in British Columbia: An Interim Evaluation

2013· article· en· W1987170937 on OpenAlexafffundabout
Tammy Stubley, Indrani Margolin, Marcela Rojas

Bibliographic record

VenueSociology Mind · 2013
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Northern British Columbia
FundersCanadian Mental Health Association
KeywordsInterimMainstreamInclusion (mineral)Mental healthPromotion (chess)SustainabilityPublic relationsHealth promotionSociologyHealth carePolitical sciencePsychologySocial scienceEcologyPolitics

Abstract

fetched live from OpenAlex

A considerable amount of research has been conducted on Aboriginal mental health and health promotion. However, implementation and impacts of culturally relevant health promotion strategies have not been equally addressed. This article provides an interim evaluation of Connecting the Dots, an innovative project designed to support and promote the mental health of Aboriginal youth and families in urban areas in British Columbia. Connecting the Dots adapted the Communities that Care (CTC) model, a prevention planning program promoting positive youth development and reducing risk factors that predict youth’s future involvement in problem behaviors. This article devotes specific attention to the necessitated adaptations of the CTC model to promote cultural relevancy in urban Aboriginal communities. Evaluation findings suggest that Aboriginal communities can successfully adopt mainstream evidence-based programming, provided that programs permit adaptations to meet the communities’ needs. For urban Aboriginal communities, programs must be re-conceptualized so that the linear, western delivery model is transformed to a holistic and circular implementation approach congruent with Aboriginal worldviews. In the Connecting the Dots project, inclusion of traditional Aboriginal practices and key Aboriginal representatives were among the most well received model adaptations. Evaluation participants reported that the adaptations made to the CTC framework have been critical to sustainability.

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)0.032
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.722

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0090.003
Scholarly communication0.0030.002
Open science0.0040.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.156
GPT teacher head0.462
Teacher spread0.305 · 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

Citations1
Published2013
Admission routes3
Has abstractyes

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