Abstract
Predictive literature on incest has focused extensively on the dynamics of the home environment, but much less attention has been paid to the individual characteristics of offenders and the victims they target. Using the 2015 dataset from the National Incident-Based Reporting System (NIBRS), a national database of criminal offenders maintained by the National Archive of Criminal Data, this dissertation sets out to complement the existing predictive framework by identifying individual characteristics associated with incest. Findings include: males constituted 93% of all biological incest offenders; females constituted 78% of all biological incest victims, the majority of which fell within fertile ages (11-40), while a substantial percentage (46%) were under age 11; forcible cases of biological incest were 4.5 times more frequent than non-forcible cases; the proportion of biological incest cases committed by a stepparent is more than 10 times greater than the proportion of stepparents in the population; incest between a biological mother and her child is the rarest type of incest on a per capita basis, with 1 case of incest occurring for every 470,180 mother-child pairs in the United States; incest between a stepfather and stepchild was the most frequent type, with 1 case occurring for every 3,384 pairs. These findings were largely consistent with an evolutionary-psychological model of incest and kin-detection.