Scott Cunningham (Applied Stats Workshop)

Date and Time

April 1, 2026
12:00PM - 01:30PM EDT

Location

CGIS Knafel Building, Room K354

Speaker & Title

Scott Cunningham (Baylor University), Correctional Officers vs. Inmates: Who Prevents Self-Harm in Prison?"

Abstract

Suicide is the leading cause of death in U.S. jails and the second-leading cause in prisons. Traditional prevention relies on correctional officers, but chronic staffing shortages—25–30 percent vacancy rates in Texas—have made surveillance-based approaches increasingly untenable. Using administrative records from the Texas Department of Criminal Justice covering 11 million inmate-months from 2017 to 2024, we evaluate two approaches to reducing suicide and self-harm. First, using panel estimators, we find that a one standard deviation increase in correctional officer staffing reduced completed suicides by 50 percent but had no effect on self-harm or suicide attempts—correctional officers intervene in acute crises but do not prevent the upstream behaviors that precede them. Second, we evaluate a peer support program in 16 prisons that pairs high-risk inmates with trained inmate volunteers. A logit model of baseline self-harm risk produced 3,614 unique fitted values which, for operational simplicity, were coarsened into 39 discrete scores; inmates above a prison-specific threshold were assigned peer support. This coarsening created quasi-randomization: inmates with identical underlying risk received different treatments depending on how rounding shifted them relative to the threshold. We exploit this variation alongside a threshold-progression difference-in-differences estimator that aggregates effects across facilities with varying entry thresholds. Peer support reduces self-harm by 30–60 percent, with effects appearing precisely where quasi-randomization is strongest and absent where assignment is nearly deterministic. Expanding staffing would cost $1.6–3.1 billion annually; peer support achieves comparable reductions at far lower cost, though it raises ethical questions about using inmate labor for institutional functions.

The Applied Statistics Workshop (Gov 3009) meets all academic year on Wednesdays. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers.

All interested Harvard affiliates are invited to attend. Lunch will be provided.