zerorelatives

Zerorelatives is a term used in genealogy, demography, and data science to describe individuals who have no known relatives within a defined dataset or social graph. The concept helps researchers distinguish between connectivity gaps caused by missing records and genuine absence of kin within the studied population. Etymologically, it combines zero with relatives to emphasize the lack of documented kin ties in the context at hand.

In practice, zerorelatives are identified by record linkage, pedigree construction, and graph analysis. Analysts classify a person as a zerorelative when no edges connect their node to other individuals in the dataset, after applying matching rules and privacy constraints. The status can reflect incomplete archival materials, recent births, migrations, or deliberate anonymization.

Uses and interpretation: Zerorelatives can highlight data quality issues and inform archival priorities, such as locating orphan records or expanding surname and location coverage. In network studies, they represent isolated nodes and can affect measures of connectivity and clustering. In privacy-preserving contexts, knowing who has no relatives in a dataset can influence risk assessments and the design of anonymization schemes.

Limitations and ethical considerations: The designation may be provisional; it may change as data are augmented. False zerorelatives can arise from mislinking or misrecording. Researchers should avoid assuming social or genetic isolation based solely on data absence, and should respect privacy concerns when handling real individuals.

See also: genealogy, kinship, social network analysis, data quality.