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Consequential Sentences: Computational Analyses of California Parole Hearing Transcripts episode artwork

Apr 23, 2025 1 hr 3 min

Consequential Sentences: Computational Analyses of California Parole Hearing Transcripts

from Matrix Podcast Hosted by Social Science Matrix

Recorded on April 1, 2025, this video features a talk by AJ Alvero, a computational sociologist at Cornell University, presenting findings from an analysis of parole hearing transcripts in California. This talk is part of a symposium series presented by the UC Berkeley Computational Research for Equity in the Legal System Training Program (CRELS), which trains doctoral students representing a variety of degree programs and expertise areas in the social sciences, computer science and statistics. The talk was co-sponsored by the UC Berkeley Berkeley Institute of Data Sciences (BIDS). Abstract In California, candidates for parole are able to present their case with the support of an attorney to commissioners appointed by the state. These hearings are professionally transcribed, making them highly amenable to a variety of social scientific questions and computational text analysis. In this talk, I will discuss a large project analyzing every parole hearing transcript in California that occurred from November 2007 until November 2019, along with a wealth of administrative data, some of which was obtained after successfully suing the California Department of Corrections and Rehabilitation (CDCR). In some of our early work, we find that patterns in the text based on the words being used and who is using them (e.g., words used by the parole commissioner) have stronger explanatory power than variables used in past studies. To conclude, I will discuss forthcoming work which takes advantage of the unique structure of the transcripts. Transcript A transcript of this talk is available at https://matrix.berkeley.edu/research-article/AJ-Alvero

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