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Record W2086879356 · doi:10.3109/10826080009147688

Community Action Research: Who Does What to Whom and Why? Lessons Learned from Local Prevention Efforts (International Experiences)

2000· review· en· W2086879356 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSubstance Use & Misuse · 2000
Typereview
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychological interventionVariety (cybernetics)Action (physics)Ethnic groupAction researchModerationPublic relationsPolitical scienceSociologyPsychologySocial psychologyPedagogyPsychiatry

Abstract

fetched live from OpenAlex

This paper describes lessons learned about community action research, drawing upon papers written and presented at a recent international conference on community action research and the prevention of alcohol and other drug problems. Projects reflected both action and evaluation research traditions and focused on a variety of issues from moderation of drinking to alcohol-related violence, and on range of target populations from youth to specific ethnic groups. The interventions described ranged from policy-based prevention to education and training and to secondary prevention and treatment. Lessons identified in the papers are discussed within three broad areas: the community targeted for change; the implementation of community projects; and community action research projects generally. The common lessons emerging from these diverse projects provide useful lessons on which to base future progress in community action research.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.656
GPT teacher head0.596
Teacher spread0.060 · 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