# Incorporating Structural Stigma into Network Analysis

## TL;DR

This paper introduces a new statistical method within network analysis to detect and analyze the active maintenance of social boundaries, such as stigma and ostracism, beyond traditional homophily effects.

## Contribution

It presents a novel statistic for ERGMs that captures boundary maintenance effects like stigma, extending the modeling of social boundary phenomena.

## Key findings

- The new statistic detects boundary maintenance effects in social networks.
- Application to a school classroom reveals gender segregation driven by boundary maintenance.
- The method distinguishes active boundary enforcement from simple homophily effects.

## Abstract

A rich literature has explored the modeling of homophily and other forms of nonuniform mixing associated with individual-level covariates within the exponential family random graph (ERGM) framework. Such differential mixing does not fully explain phenomena such as stigma, however, which involve the active maintenance of social boundaries by ostracism of persons with out-group ties. Here, we introduce a new statistic that allows for such effects to be captured, making it possible to probe for the potential presence of boundary maintenance above and beyond simple differences in nomination rates. We demonstrate this statistic in the context of gender segregation in a school classroom.