TY  - JOUR
PY  - 2020//
TI  - Learning to kill: why a small handful of counties generates the bulk of US death sentences
JO  - PLoS one
A1  - Baumgartner, Frank R.
A1  - Box-Steffensmeier, Janet M.
A1  - Campbell, Benjamin W.
A1  - Caron, Christian
A1  - Sherman, Hailey
SP  - e0240401
EP  - e0240401
VL  - 15
IS  - 10
N2  - We demonstrate strong self-referential effects in county-level data concerning use of the death penalty. We first show event-dependency using a repeated-event model. Higher numbers of previous events reduce the expected time delay before the next event. Second, we use a cross-sectional time-series approach to model the number of death sentences imposed in a given county in a given year. This model shows that the cumulative number of death sentences previously imposed in the same county is a strong predictor of the number imposed in a given year. <br><br>RESULTS raise troubling substantive implications: The number of death sentences in a given county in a given year is better predicted by that county's previous experience in imposing death than by the number of homicides. This explains the previously observed fact that a large share of death sentences come from a small number of counties and documents the self-referential aspects of use the death penalty. A death sentencing system based on racial dynamics and then amplified by self-referential dynamics is inconsistent with equal protection of the law, but this describes the United States system well.<p />  <p>Language: en</p>
LA  - en
SN  - 1932-6203
UR  - http://dx.doi.org/10.1371/journal.pone.0240401
ID  - ref1
ER  -