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Exploring community engagement in place-based approaches in areas of poor health and disadvantage: A scoping review

2023· review· en· W4366382537 on OpenAlexaboutno aff
Tanya Rong, Eli Ristevski, Matthew Carroll

Bibliographic record

VenueHealth & Place · 2023
Typereview
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantageIndigenousCommunity engagementInclusion (mineral)Community healthQualitative researchSociologyPublic relationsPolitical sciencePublic healthMedicineNursingSocial science

Abstract

fetched live from OpenAlex

A scoping review was conducted to explore the characteristics, barriers, and enablers of community engagement in place-based approaches to improving health outcomes in a designated area of poor health and disadvantage. The Joanna Briggs Institute methodology for scoping reviews was used. Forty articles met the inclusion criteria of which 31 were conducted in the United Kingdom, United States, Canada, or Australia, and 70% used qualitative methods. The health initiatives were delivered in multiple settings including neighbourhoods, towns, and regions and with a range of population groups including Indigenous and migrant communities. Trust, power, and cultural considerations were the most significant barriers and enablers to community participation in place-based approaches. Developing trust is key to success in community-led, place-based initiatives.

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)0.019
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0140.018
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.721
GPT teacher head0.559
Teacher spread0.161 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations74
Published2023
Admission routes1
Has abstractyes

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