Post-Doctoral Researcher,
UC Berkeley
Punishment, politics, and democracy
Hello!
My research lies at the intersection of democratic accountability, public perception of justice, and the changing climate of criminal legal politics.
Of particular interest in my work is the tangible impact of local elections and voter preferences on law enforcement practices and prosecutorial conduct. My research illuminates how these variables drive changes in local incarceration rates, providing a clearer understanding of crime and justice politics at a time when public sentiment is increasingly in favor of legal reform.
I'm passionate about unraveling these interconnected themes to contribute to ongoing dialogues surrounding progressive prosecution and the push towards a less punitive approach to justice.
I hope my research will not only contribute to academic discourse but also inform policy decisions and foster a more equitable and responsive justice system.
BIO
LL.B, LL.M, Ph.D.
My journey began with a fascination for justice, leading me to law school to study jurisprudence and socio-legal theory. Further inspired by a stint at the Israeli National Public Defense Department, I then chose to delve deeper into the political, structural, and psychological intricacies of the criminal legal system at UC Berkeley.
Current Works in Progress:
Under review (R&R)
Perceived Algorithmic Legitimacy in the Administrative State
Algorithmic decision-making tools are changing the operation of the Administrative State, as machine learning models and other forms of automation proliferate in the government. Administrative legitimacy, an already contentious matter, is being further questioned with concerns regarding algorithmic decision-making. Can agencies maintain or even reinforce legitimacy while relying on algorithms? A burgeoning literature puts forth an array of proposals to improve administrative accountability and legitimacy of algorithmic decision-making tools, yet the efficacy of improving public perceptions of legitimacy has not been thoroughly empirically tested. This article uses a conjoint survey experiment (N=499) to test which aspects of a governmental program that employs an algorithmic tool affect the public’s perceptions of legitimacy. Moving beyond direct human-algorithm comparisons toward more complex attributes, this study applies and contrasts two theoretical frameworks: Procedural Justice and Algorithmic Governance. Also, the study unpacks notions of fairness and efficiency to construct a more nuanced model of algorithmic legitimacy. We find that a positive effect on perceived legitimacy derives from communicating the algorithmic procedure: notice about the use of an algorithm, human involvement in algorithmic decision-making, decision explanation, and hearing by request. We also find that respondents consider the policy domain and deem the use of algorithms in the criminal justice context as less fair than other domains but not necessarily less efficient. Finally, we find that perceptions of fairness differ from perceptions of efficiency.
Under review
(R&R)
Intensive and Extensive Margins of Legal Reform
Decades of support for tough-on-crime policies have led the United States to lock up more people per capita than most countries worldwide. In recent years, however, voters have become less supportive of such policies. Under which conditions do voters support progressive reform? Are voters willing to support politicians who are not tough on crime? I develop a theory of prosecutor elections voting behavior using data from a recent recall election and test it on a national sample. Recently, San Francisco voters, who are seen as among the more progressive voters in the country, recalled a leading progressive prosecutor. The recall election is a rare opportunity to examine voters' revealed preferences in a setting that is becoming pivotal for the politics of crime and justice. I argue that there are political majorities in favor of reforming the intensity of the criminal legal system, not its extent; voters support reducing outcomes' harshness but not limiting the scope of prosecuted behavior. I show that support for reducing the intensity of the criminal legal system is wide and cuts across voters with different political attitudes. On the other hand, support for reducing the extensiveness of the criminal legal system is narrow. I conclude that to gain political approval, politicians who intend to end Mass Incarceration should focus on reducing the criminal legal system's intensive margin, not its extensive margin.
Under review
(R&R)
Why Support Crime Control Policy Reform? Group Cues and Informational Persuasion
Criminal justice policy reform is crucial for a nation grappling with public safety concerns and decades of mass incarceration, which increased racial disparities. In this article, I develop a theory of racial and criminal justice cognitive relatedness to explain why people support different policy responses to crime. This study investigates the factors that shape public attitudes toward criminal justice policy reform, focusing on the role of dispositional racial attitudes and political and racial group cues. Employing a conjoint design and a follow-up survey experiment, I demonstrate that people's dispositions toward racial and political groups affect their criminal justice policy preferences. Both people of color and white respondents follow cues from Black voters, with racial attitudes playing an important moderating role. Furthermore, I find little evidence for partisan cues' influence on support for reform. These findings have fundamental implications for political activists and their efforts to support criminal justice reform campaigns.
Under review
(R&R)
The Effect of Causal Attribution on Dangerousness and Race Perceptions
What affects perceptions of dangerousness? Assessing whether an individual poses a risk to society is a routine activity throughout the criminal legal system. Decision makers may consider professional risk assessments, but the decision is subjective and might rely on heuristics. Psychology research finds that the Fundamental Attribution Error affects perceptions of morality through the belief that the actions of others are the direct outcome of personality or character. However, less is known about its effect on perceptions of dangerousness. Across two online experiments (N = 1005 and N = 276), I examine how a putative parole candidate’s choice to attribute their crime to dispositional or situational factors affects people’s perceptions of dangerousness and racial classification. The studies show that the use of situational attribution increased perceptions of dangerousness when the participant did not accept the situational account of the candidate as valid. Moreover, attributing the causes of crime to the situation and the environment predicts perceiving the parole candidate as a person of color. Understanding what affects perceptions of dangerousness is crucial for the criminal legal system, and policy suggestions are discussed.
The Effect of DA Elections on Public Safety
What is the effect of a political struggle between a district attorney (DA) and a police department on public safety? During the tenure of Chesa Boudin as San Francisco’s DA, a political rivalry developed between the district’s prosecutors and police department. Typically partners, the DA’s office under Boudin's leadership vowed to tighten up police accountability in response to misconduct allegations. In 2022 a political campaign to recall Boudin succeeded, resulting in Boudin’s electoral defeat (June) and leave of office (July). In this paper, we estimate the effect of the police department taking sides in a political campaign. We show that there was a sharp change in the jail population after the recall and argue that it is attributed to changes in police behavior, not DA preferences: an increase in crime reports, in police stops for traffic and public order offenses, and in arrests. This paper suggests that police departments react to political pressure and might influence local elections.