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Record W2028893186 · doi:10.1136/ip.2010.029215.321

Listen and learn: working with ethno-cultural communities to share injury prevention

2010· article· en· W2028893186 on OpenAlexaffabout
Pamela Fuselli

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsTD Bank Group
Fundersnot available
KeywordsOutreachPublic relationsEthnic groupPoison controlPopulationSuicide preventionCapacity buildingCommunity engagementMedicinePolitical scienceBusinessEnvironmental health

Abstract

fetched live from OpenAlex

Safe Kids Canada launched the Ethno-Cultural Program targeted towards providing injury prevention resources for diverse communities in Canada. Goals To establish a national injury prevention programme that translates knowledge to diverse population in Canada. Identified communities have access to culturally appropriate injury prevention resources for the purpose of influencing behaviour to reduce the burden of injury. To establish collaborative relationships with appropriate key stakeholders, such as ethno-cultural agencies who serve diverse communities. The programme has successfully developed and distributed culturally relevant safety messages for parents and community partners for the purpose of raising awareness and reducing child injuries within ethnic communities in the Greater Toronto Area – Chinese, Portuguese and Punjabi – but can be utilised across Canada. This programme sought to go beyond simple translation from one language to another, by instead engaging the communities who would benefit from injury prevention outreach in the assessment and development of the final resources. Key learnings showed that this method was effective and welcomed by the communities because of their involvement and the collaborative approach we adopted. Extensive cultural media outlets picked up the information and resulted in two million media impressions, 45 000 resources distributed and 100 community leaders engaged who now have increased capacity to provide culturally appropriate resources. This presentation will share the focus group formats, important lessons learned and the resulting resources now available in 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.901

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.364
Teacher spread0.307 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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