English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Bayesian Improved Surname Geocoding (BISG) is a ubiquitous tool forpredicting race and ethnicity using an individual's geolocation and surname.BISG assumes that in the United States population, surname and geolocation areindependent given a particular race or ethnicity. This assumption appears tocontradict conventional wisdom including that people often live near theirrelatives and others with similar demographic features. Here we demonstratethat this independence assumption results in systematic biases for minoritysubpopulations. For example, in areas with large White populations, BISG errorsare large in magnitude and tend to have the same sign for given minoritysubpopulations. We introduce a simple raking-based prediction algorithm thatoffers a significant improvement over BISG and we validate our algorithm onstates' voter registration lists. The proposed improvement and the inaccuraciesof BISG generalize to applications in election law, health care, finance, tech,law enforcement and many other fields.

BISG: When inferring race or ethnicity, does it matter that people often live near their relatives?