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Record W2755095372 · doi:10.1111/dar.12599

Research into action? The Eastside Illicit Drinkers Group for Education's (EIDGE) experiences as a community‐based group in Vancouver, Canada

2017· article· en· W2755095372 on OpenAlexaffabout
Loretta Jackson Brown, John Skulsh, Rob Morgan, Ron Kuehlke, Brittany Graham

Bibliographic record

VenueDrug and Alcohol Review · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCentre for Drug Research and Development
Fundersnot available
KeywordsAction (physics)Alcohol educationPsychologyPolitical sciencePublic relationsGerontologyMedical educationPsychiatryLibrary scienceMedicine

Abstract

fetched live from OpenAlex

The Eastside Illicit Drinkers Group for Education has been supportive of research dedicated to establishing the effectiveness of Managed Alcohol Programs since its inception. Dedicated funding for MAPs in Vancouver, British Columbia is contingent on the research demonstrating that alcohol-related harms are reduced while participating in a Managed Alcohol Program. The Eastside Illicit Drinkers Group for Education understands the need for evidence-based research but we are critical of how much research is needed before sustainable funding can be established for these innovative programs.

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)0.016
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.285
Threshold uncertainty score0.572

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0060.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.171
GPT teacher head0.526
Teacher spread0.354 · 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 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

Citations10
Published2017
Admission routes2
Has abstractyes

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