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Record W4380422479 · doi:10.1177/17579759231176293

Hands-on-ground in a new country: a community-based participatory evaluation with immigrant communities in Southern Alberta

2023· article· en· W4380422479 on OpenAlexafffundabout
Ulises Charles-Rodriguez, Aiat Aborawi, Kamal Khatiwada, Ashmita Shahi, Silvia Koso, Savanna Prociw, Christa Sanford, Richard Larouche

Bibliographic record

VenueGlobal Health Promotion · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsLethbridge CollegeUniversity of CalgaryUniversity of Lethbridge
FundersUniversity of Lethbridge
KeywordsParticipatory action researchCommunity-based participatory researchImmigrationPsychological interventionSocializationStakeholderFocus groupPublic relationsContext (archaeology)Inclusion (mineral)RefugeeCommunity engagementCitizen journalismCommunity organizationPolitical scienceNursingSociologyPsychologyMedicineGeographySocial psychology

Abstract

fetched live from OpenAlex

Immigrants experience a high risk of mental health deterioration following settlement in Canada. Immigrant communities benefit from health-promoting interventions that stimulate social inclusion and belonging as protective factors. In this context, community gardens have been recognized as interventions that promote healthy behaviours, place attachment and belonging.This article summarizes our experience conducting a community-based participatory evaluation (CBPE), engaging community stakeholders in planning, implementing and evaluating a community garden for immigrants. We conducted a CBPE to provide relevant and timely feedback to inform programme adaptation and development. Participants, interpreters and organizers were engaged through surveys, focus groups and semi-structured interviews. Participants expressed a range of motivations, benefits, challenges and recommendations. The garden was a place that fostered learning and promoted healthy behaviours, including physical activity and socialization. However, there were challenges in organization and communication with participants. Findings were used to adapt the activities to immigrants' needs and expand the programming of collaborating organizations. Stakeholder engagement facilitated capacity building and direct use of findings. This approach may catalyse sustainable community action with immigrant communities.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.099
GPT teacher head0.333
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2023
Admission routes3
Has abstractyes

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