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Record W4408169897 · doi:10.1038/s41531-025-00891-7

Race and ethnicity matter! Moving Parkinson’s risk research towards diversity and inclusiveness

2025· review· en· W4408169897 on OpenAlexafffund
Sara Siddiqi, Z Ortiz, Stephanie Simard, Juan Li, Kamaya Lawrence, Melissa Redmond, Julianna J. Tomlinson, Michael G. Schlossmacher, Natalina Salmaso

Bibliographic record

Venuenpj Parkinson s Disease · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsCarleton UniversityOttawa HospitalUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsRace (biology)Ethnic groupParkinson's diseaseDiversity (politics)MedicineGerontologyPsychologySociologyGender studiesDiseaseInternal medicineAnthropology

Abstract

fetched live from OpenAlex

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that shows considerable heterogeneity of risk factors however, the degree to which race/ethnicity has been actively pursued in PD risk research is unknown. We examined PD literature from 2000-24 and found that less than half accounted for race/ethnicity and only 4.8% of n = 1142 articles included ethno-racial factors as an integral part of the analysis. This demonstrates that race/ethnicity has been critically understudied in PD and further studies that examine ethno-racial contributions to risk for PD are warranted.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.355
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2025
Admission routes2
Has abstractyes

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