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Avoiding bias when inferring race using name-based approaches

PLOS ONE(2022)10.1371/journal.pone.0264270Source: DataRank Database

Avoiding bias when inferring race using name-based approaches is a research paper published in PLOS ONE (2022). On theSindex it has a DataRank of 1.5. It has been cited 54 times, with 50 citing works in its 1-hop citation network.

N/A

1.5DataRank · unranked

Scored on demand from live citation data

Open Access54 citations · 50 citing works in its network

Free full text

Cite:

Linked data & code

Avoiding bias when inferring race using name-based approaches · arXiv

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 15.43)OA: goldTopics (27)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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DataRank Breakdown

Base Score 39%Citation Network 61%

Base Score Contribution

0.601

From this paper's citation signal

Citation Network Contribution

0.925

From 33 citing papers with measurable signal

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Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 50 citers.

Name-based demographic inference and the unequal distribution of misrecognition
Nature Human Behaviour202378 citations41 referencesContributes 0.107
Analysis of science journalism reveals gender and regional disparities in coverage
bioRxiv (Cold Spring Harbor Laboratory)202110 citations31 referencesContributes 0.077
Analysis of science journalism reveals gender and regional disparities in coverage
eLife20235 citations26 referencesContributes 0.069
Name-Based Demographic Inference and the Unequal Distribution of Misrecognition
202221 citations47 referencesContributes 0.066
Unveiling the ethical void: Bias in reference citations and its academic ramifications
Current Research in Physiology20245 citations30 referencesContributes 0.060

Authors (7)

Will Hulsey,Vincent Larivière ORCID,Cassidy R. Sugimoto ORCID,Dakota Murray ORCID,Alexis T. Bell ORCID

Live enrichment

PubMed:35231059 OpenAlex:https://openalex.org/W3158739288

Fonds National de la Recherche Luxembourg

Grant: PRIDE17/12252781

Canada Research Chairs

Grant: 950-231768

FWCI

15.43

Citation Percentile

1.0%

Citation Trend

2021

2022

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://doi.org/10.1371/journal.pone.0264270

publisherhttps://doi.org/10.1371/journal.pone.0264270

publisherhttps://dx.plos.org/10.1371/journal.pone.0264270

repositoryhttps://pubmed.ncbi.nlm.nih.gov/35231059

repositoryhttp://arxiv.org/abs/2104.12553

Fields of Study

Names, Identity, and Discrimination ResearchRacial and Ethnic Identity ResearchGlobal Cancer Incidence and ScreeningBiasCensusesEthnicityHumansNamesUnited States

MeSH Terms

EthnicityHumansNamesUnited StatesBiasCensuses

Keywords

InferenceRace (biology)Imputation (statistics)Computer scienceData scienceRacial biasEconometricsArtificial intelligenceMachine learningMathematicsSociologyMissing data

Sustainable Development Goals

SDG 0: Reduced inequalities

Avoiding bias when inferring race using name-based approaches

10.48550/arxiv.2104.12553arXiv