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Record W4415463712 · doi:10.1080/07347324.2025.2569874

The Collegiate Recovery Research Collaborative: New Directions for Collegiate Recovery Science

2025· article· en· W4415463712 on OpenAlexaff
Thomas Bannard, Dominiquie “Cj” Clemmons-James, Meredith W. Francis, Michael J. Broman, Michael J. Cleveland, Waltrina DeFrantz-Dufor, Danielle M. Dick, Emily A. Hennessy, Konul C. Karimova, Onawa LaBelle, Jessica McDaniel, Chelsea D. Shore, Rebecca L. Smith, Jason Whitney, Yali Yang, Victoria Burns

Bibliographic record

VenueAlcoholism Treatment Quarterly · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of CalgaryUniversity of Windsor
Fundersnot available
KeywordsData collectionMEDLINE

Abstract

fetched live from OpenAlex

The Collegiate Recovery Research Collaborative (CRRC) is a diverse group of academics and practitioners who have lived experience of recovery or who identify as allies, and addresses the lack of diverse, transdisciplinary research communities in addiction recovery. This article describes the process the CRRC used to facilitate a recent retreat focused on collegiate recovery research as a novel, replicable framework for identifying exploratory research ideas within the recovery community. This article also summarizes the insights and ideas derived from the retreat as the product of a collaborative and intentionally-fostered intellectual exercise, and identifies actionable next steps in collegiate recovery 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.

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)0.437
metaresearch head score (Gemma)0.330
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.437
Threshold uncertainty score0.694

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4370.330
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0150.012
Science and technology studies0.0290.103
Scholarly communication0.0560.089
Open science0.0140.048
Research integrity0.0260.037
Insufficient payload (model declined to judge)0.0150.003

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 head0.412
GPT teacher head0.658
Teacher spread0.247 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2025
Admission routes1
Has abstractyes

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