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Record W4376649187 · doi:10.1002/cesm.12012

The equity group: Supporting Cochrane's social responsibility of improving health equity

2023· article· en· W4376649187 on OpenAlexaff
Roses Parker, Jennifer Petkovic, Jordi Pardo Pardo, Andrea Darzi, Omar Dewidar, Joanne Khabsa, Elizabeth Kristjansson, Tamara Lotfi, Olivia Magwood, Lawrence Mbuagbaw, Kevin Pottie, Alison Riddle, Ammar Saad, E. Tomlinson, Peter Tugwell, Vivian Welch

Bibliographic record

VenueCochrane Evidence Synthesis and Methods · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsWestern UniversitySt. Joseph’s Healthcare HamiltonMcMaster UniversityImpactOttawa HospitalBruyèreUniversity of Ottawa
Fundersnot available
KeywordsEquity (law)Health equityBusinessPublic relationsEquity riskPsychologyPolitical scienceFinancePrivate equityHealth careLaw

Abstract

fetched live from OpenAlex

Introduction: Health equity is a moral and ethical imperative for clinicians, researchers, policymakers, and all who use health research. Both Cochrane and the Campbell Collaboration have focused on health equity for many years. Methods: The new Equity Group will continue and expand this work by designing a program of projects aiming to (1) promote equity in the evidence base, (2) ensure equitable processes for stakeholder engagement, (3) produce high-priority, equity-focused evidence syntheses, (4) build capacity for equity design, analysis, and reporting, and (5) promote equity in implementation tools. Results: We will build on our current network of collaborators and create a group structure striving to recruit across the PROGRESS-Plus characteristics. Conclusion: We invite readers to join our cause and contribute wherever they are able. Together, we can help Cochrane achieve its social responsibility of improving health equity at a planetary level.

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)0.585
metaresearch head score (Gemma)0.804
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.415
Threshold uncertainty score0.512

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5850.804
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0150.013
Science and technology studies0.0080.021
Scholarly communication0.0330.024
Open science0.0120.029
Research integrity0.0650.039
Insufficient payload (model declined to judge)0.0240.006

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 head0.585
GPT teacher head0.727
Teacher spread0.142 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainEvaluation
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

Citations6
Published2023
Admission routes1
Has abstractyes

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