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Record W1559607143

Building collective efficacy and sustainability into a community collaborative: Community solution to gang violence

2011· article· en· W1559607143 on OpenAlexaboutno aff
Jana Grekul

Bibliographic record

VenueJournal of gang research · 2011
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityScope (computer science)Collective efficacyPublic relationsSummitCollaborative networkSuicide preventionPoison controlPolitical scienceSociologyEngineeringMedicineEnvironmental healthComputer scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

In existence for over 6 years, the Community Solution to Gang Violence (CSGV) is a community-based initiative in Edmonton, Alberta, Canada that includes over 30 organizations working together on a strategic approach to prevent youth gang involvement. As a follow-up to an earlier article, this paper explores the viability of CSGV's future by assessing its collective efficacy and issues relating to sustainability by drawing on documents and records produced by the CSGV project manager and interviews with working group members. CSGV members continue to express a commitment to the initiative's objectives, but the scope of the collaborative has reached a point where change may be necessary in order to access the kinds of funds necessary to sustain its momentum. Using the four pillars of the collaborative, knowledge translation, engaged network, community awareness and support from community leaders and funders, this paper provides a look at the collective efficacy of CSGV including a discussion of some of its successes and the challenges it faces, through the insights of a sample of its members. The paper concludes with speculation on the sustainability of the collaborative.

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)0.031
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.008
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 head0.259
GPT teacher head0.558
Teacher spread0.298 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2011
Admission routes1
Has abstractyes

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