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Record W4392172106 · doi:10.2139/ssrn.4699442

Centering Racial Health Equity in Systematic Reviews Paper 5: A Methodological Overview of Methods and Interventions

2024· article· en· W4392172106 on OpenAlexaff
Vivian Welch, Omar Dewidar, Anita Rizvi, Mostafa Bondok, Yuewen Pan, Hind Sabri, Adedeji Adewale, Elizabeth Tanjong Ghogomu, Elizabeth Terhune, Damian Francis, Ana Beatriz Pizarro, Tiffany Duque, Patricia Heyn, Dru Riddle, Nila A Sathe, Meera Viswanathan

Bibliographic record

VenueSSRN Electronic Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoUniversity of OttawaBruyèreÉlisabeth Bruyère Hospital
Fundersnot available
KeywordsPsychological interventionHealth equityEquity (law)Systematic reviewActuarial scienceManagement sciencePolitical sciencePsychologyBusinessEconomicsMedicineMEDLINEHealth careEconomic growthNursingLaw

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.488
metaresearch head score (Gemma)0.652
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.512
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4880.652
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0120.024
Bibliometrics0.0250.024
Science and technology studies0.0040.006
Scholarly communication0.0130.010
Open science0.0040.011
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0140.002

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 head0.518
GPT teacher head0.669
Teacher spread0.151 · 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 designSystematic review
DomainMethods
GenreMethods

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

Citations2
Published2024
Admission routes1
Has abstractno

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