This is an overview based on the article, "The Artificially Unintelligent Data Double" (https://doi.org/10.21428/cb6ab371.39657484). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com.

The paper maps core elements of GST onto identifiable neuropsychological processes, such as sensitivity to rewards, sensitivity to social status, and cognitive control, towards a more comprehensive understanding of individual responses to social and environmental strains.

This is an overview based on the article, "Evaluating Large Language Models as Judicial Decision-Makers" (https://doi.org/10.21428/cb6ab371.4933a431 ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. Intro: Can Artificial Intelligence fix the "lawlessness" and inconsistency found in criminal sentencing? This video breaks down a groundbreaking 2026 study published in Justice Quarterly that evaluates whether Large Language Models (LLMs) can serve as effective judicial decision-makers. What’s Inside: Researchers compared the sentencing decisions of 123 retired judges against three major AI models: GPT-4o, Gemini-2.0-Flash, and Claude-3.5-Sonnet. Using fictional cases involving violent assault and sexual offenses, the study tested whether AI could reduce sentencing disparity without losing accuracy. Key Findings Covered: • Inconsistency in Law: Historical data shows human judges often impose vastly different sentences for similar cases, a problem known as "noise". • AI Consistency: The study found that LLMs produced significantly lower sentence disparity than human judges, meaning they were more consistent in their rulings. • Accuracy: When using the average human sentence as a benchmark, AI models deviated less from the consensus than the judges themselves did. • Prompting Matters: The video explains how "Few-Shot" and "Chain-of-Thought" prompting strategies helped align AI decisions with judicial norms. Conclusion: While AI offers a promising tool to reduce unwarranted disparities, ethical questions regarding transparency, bias, and the "human element" of justice remain. Watch to understand the future of AI in the courtroom. Sources: Based on the paper "Evaluating Large Language Models as Judicial Decision-Makers" by Oren Gazal Ayal, Zohar Elyoseph, and Adir Solomon (2026)

This is an overview based on the article, "Evaluating Large Language Models as Judicial Decision-Makers" (https://doi.org/10.21428/cb6ab371.4933a431 ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. Intro: Can Artificial Intelligence fix the "lawlessness" and inconsistency found in criminal sentencing? This video breaks down a groundbreaking 2026 study published in Justice Quarterly that evaluates whether Large Language Models (LLMs) can serve as effective judicial decision-makers. What’s Inside: Researchers compared the sentencing decisions of 123 retired judges against three major AI models: GPT-4o, Gemini-2.0-Flash, and Claude-3.5-Sonnet. Using fictional cases involving violent assault and sexual offenses, the study tested whether AI could reduce sentencing disparity without losing accuracy. Key Findings Covered: • Inconsistency in Law: Historical data shows human judges often impose vastly different sentences for similar cases, a problem known as "noise". • AI Consistency: The study found that LLMs produced significantly lower sentence disparity than human judges, meaning they were more consistent in their rulings. • Accuracy: When using the average human sentence as a benchmark, AI models deviated less from the consensus than the judges themselves did. • Prompting Matters: The video explains how "Few-Shot" and "Chain-of-Thought" prompting strategies helped align AI decisions with judicial norms. Conclusion: While AI offers a promising tool to reduce unwarranted disparities, ethical questions regarding transparency, bias, and the "human element" of justice remain. Watch to understand the future of AI in the courtroom. Sources: Based on the paper "Evaluating Large Language Models as Judicial Decision-Makers" by Oren Gazal Ayal, Zohar Elyoseph, and Adir Solomon (2026)

Large Language Models (LLMs) are increasingly shaping various domains, yet their ability to align with human judgment remains a critical challenge. This study explores the extent to which LLMs can serve as judicial decision-makers by comparing their sentencing decisions to ...

This study explores the adaptive mechanisms and survival strategies deployed by incarcerated individuals during the Lee Prison Riot of April 15, 2018. Drawing solely on in-depth interviews with 25 incarcerated men (predominantly Black, aged 25–61) at Lee Correctional ...

The misuse of law firm pooled client (or trust) accounts is identified as a key money laundering risk for the legal profession. However, this risk may be mitigated in the UK by the multi-layered regulatory framework that has evolved to prevent the misuse of such accounts for ...

This is an overview based on the article, "Recalibrating the risk of false confession wrongful convictions: Interrogation tactics and inverse probability" (https://doi.org/10.21428/cb6ab371.59ff4386 ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. How risky are standard police interrogation tactics? While false confession wrongful convictions (FCWCs) are tragic, new research suggests the probability of them happening during lawful interrogations is much lower than previously thought. This video breaks down the 2026 study by Scott M. Mourtgos and Ian T. Adams, published in the Journal of Criminal Justice, which uses inverse probability logic to find the real numbers behind the controversy. [Key Takeaways] In this video, we cover: • The "Outcome Selection" Problem: Why looking only at known wrongful convictions inflates risk estimates and ignores the vast majority of accurate confessions. • The 1% Finding: Why the median posterior probability of a lawful tactic leading to a wrongful conviction clusters near 1%, rather than being a widespread systemic failure. • Ecological Validity: Why laboratory experiments like the "ALT-key" paradigm may not apply to real-world custodial interrogations. • The Acceptability Curve: Understanding the trade-off between the harm of wrongful convictions and the harm of failing to convict the guilty. Study Context: Critics often argue for banning accusatory methods based on cases where things went wrong. However, this study argues that without accounting for the "base rate" of wrongful convictions and the frequency of successful interrogations, we cannot accurately estimate risk. Using Monte Carlo simulations, the authors demonstrate that even when multiple tactics are used, the risk remains empirically low. Source: Mourtgos, S. M., & Adams, I. T. (2026). Recalibrating the risk of false confession wrongful convictions: Interrogation tactics and inverse probability. Journal of Criminal Justice.

False confession wrongful convictions (FCWCs) are a serious failure of the criminal justice system. Although scholars have identified interrogation tactics thought to elevate this risk, existing research rarely estimates the population-level probability that legally ...

This is an overview based on the article, "Recalibrating the risk of false confession wrongful convictions: Interrogation tactics and inverse probability" (https://doi.org/10.21428/cb6ab371.59ff4386 ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. How risky are standard police interrogation tactics? While false confession wrongful convictions (FCWCs) are tragic, new research suggests the probability of them happening during lawful interrogations is much lower than previously thought. This video breaks down the 2026 study by Scott M. Mourtgos and Ian T. Adams, published in the Journal of Criminal Justice, which uses inverse probability logic to find the real numbers behind the controversy. [Key Takeaways] In this video, we cover: • The "Outcome Selection" Problem: Why looking only at known wrongful convictions inflates risk estimates and ignores the vast majority of accurate confessions. • The 1% Finding: Why the median posterior probability of a lawful tactic leading to a wrongful conviction clusters near 1%, rather than being a widespread systemic failure. • Ecological Validity: Why laboratory experiments like the "ALT-key" paradigm may not apply to real-world custodial interrogations. • The Acceptability Curve: Understanding the trade-off between the harm of wrongful convictions and the harm of failing to convict the guilty. Study Context: Critics often argue for banning accusatory methods based on cases where things went wrong. However, this study argues that without accounting for the "base rate" of wrongful convictions and the frequency of successful interrogations, we cannot accurately estimate risk. Using Monte Carlo simulations, the authors demonstrate that even when multiple tactics are used, the risk remains empirically low. Source: Mourtgos, S. M., & Adams, I. T. (2026). Recalibrating the risk of false confession wrongful convictions: Interrogation tactics and inverse probability. Journal of Criminal Justice.

This is an overview for the grant proposal, "Building Academic Personal Websites on Arweave with Portal)" (https://www.crimrxiv.com/pub/8wx7rnxp). We created this video with the AI tool Google NotebookLM. The funding opportunity is the Spark DeSci Fund for Radical Researchers (https://artizen.fund/index/mf/spark-desci-fund-for-radical-researchers?season=5).

This is an overview based on the article, "Unforeseen shock: How perceived vulnerability shapes the psychological impact of interpersonal victimization" (https://doi.org/10.21428/cb6ab371.6d74933a ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. Panel studies often show that the average effects of victimization on well-being are modest, but this average conceals substantial variation. This research investigates whether the psychological impact of a crime depends on what the victim expected to happen to them beforehand. Key Concepts Covered: The video breaks down two competing theoretical accounts tested in the study: 1. Expectation-Violation (Shattered Assumptions): The idea that victimization is an unexpected shock that violates core beliefs about safety, predicting that those with low perceived vulnerability will suffer the most. 2. Stress-Sensitization: The idea that victimization layers onto existing strain, predicting that those who already felt vulnerable will suffer the most. Study Findings: Using two-wave panel data from 2,932 adults in Germany, the researchers found that interpersonal victimization generally had modest average effects on well-being. However, the data supported the expectation-violation account: victims who perceived their risk as low prior to the crime showed larger negative changes in their emotional state compared to those who already perceived themselves as medium- or high-risk. Reference: Kaiser, F., Jackson, J., Oberwittler, D., & Huss, B. (2026). Unforeseen shock: How perceived vulnerability shapes the psychological impact of interpersonal victimization.

Criminologists regularly teach material that some students may find difficult or distressing, yet debate continues over which topics are considered sensitive and how they should be taught to minimize harm. To understand which topics criminology educators in Australia and ...

How the UK government has politicised asylum by categorising Albanian asylum-seekers as ‘criminals’ and Albania as a ‘safe’ country to advance an immigration deterrence agenda remains unresearched. We use agenda-setting and policy framing analytical insights to explain how ...

This is an overview based on the article, "Bounded Engagement and Institutional Interdependency: Exploring Formerly Incarcerated Adults’ (Non)Engagement Experiences and Perceptions" (https://doi.org/10.21428/cb6ab371.8f91c230 ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. Description: This video explores the complex reality of "bounded engagement" and how formerly incarcerated adults navigate formal institutions like banks, healthcare, and the labor market. Based on a 2026 study by Denver, Navarro, and Brunson involving nearly 100 interviews, we discuss why non-engagement is often caused by administrative burdens rather than voluntary opting out. Key Topics Covered in This Video: • Bounded Engagement defined: How people engage with institutions when possible but find informal alternatives when barriers exist. • Institutional Interdependency: How a barrier in one area (like lacking a state ID) creates roadblocks in others (like getting a job or credit card). • Financial Exclusion: Why minimum balance requirements push people toward "second chance banking" apps like Chime and Cash App. • The "SSI Dilemma": How income restrictions on government benefits can discourage formal employment. • System Avoidance: Why fear of surveillance is usually limited to specific institutions, such as those related to wage garnishment for child support. • Healthcare Success: How policy changes in Massachusetts (MassHealth) have led to high medical engagement among returning citizens. Reference: Denver, M., Navarro, O., & Brunson, R. K. (2026). Bounded Engagement and Institutional Interdependency: Exploring Formerly Incarcerated Adults’ (Non)Engagement Experiences and Perceptions. Journal of Research in Crime and Delinquency. #Criminology #Reentry #SocialJustice #CriminalJusticeReform #Sociology #BoundedEngagement #AdministrativeBurden

This is an overview based on the article, "Unforeseen shock: How perceived vulnerability shapes the psychological impact of interpersonal victimization" (https://doi.org/10.21428/cb6ab371.6d74933a ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. Panel studies often show that the average effects of victimization on well-being are modest, but this average conceals substantial variation. This research investigates whether the psychological impact of a crime depends on what the victim expected to happen to them beforehand. Key Concepts Covered: The video breaks down two competing theoretical accounts tested in the study: 1. Expectation-Violation (Shattered Assumptions): The idea that victimization is an unexpected shock that violates core beliefs about safety, predicting that those with low perceived vulnerability will suffer the most. 2. Stress-Sensitization: The idea that victimization layers onto existing strain, predicting that those who already felt vulnerable will suffer the most. Study Findings: Using two-wave panel data from 2,932 adults in Germany, the researchers found that interpersonal victimization generally had modest average effects on well-being. However, the data supported the expectation-violation account: victims who perceived their risk as low prior to the crime showed larger negative changes in their emotional state compared to those who already perceived themselves as medium- or high-risk. Reference: Kaiser, F., Jackson, J., Oberwittler, D., & Huss, B. (2026). Unforeseen shock: How perceived vulnerability shapes the psychological impact of interpersonal victimization.

This is an overview based on the article, "Creating criminology podcasts with generative artificial intelligence, storing them on Web3, and sharing them open access: A contribution to utilitarian digital pedagogy (Part I - conceptual and theoretical issues)" (https://doi.org/10.21428/cb6ab371.0753be51). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com.

Quantitative studies of institutional (non)engagement are limited by available measures and temporal ordering concerns. Using unique and detailed qualitative data, we examine (non)engagement behaviors and perceptions among formerly incarcerated adults.

Current workforce shortages have led many police agencies to evaluate their hiring standards to increase the number of candidates they receive. Although getting more individuals into the profession is crucial, it should not come at the expense of losing trust and legitimacy ...

This is an overview based on the article, "Bounded Engagement and Institutional Interdependency: Exploring Formerly Incarcerated Adults’ (Non)Engagement Experiences and Perceptions" (https://doi.org/10.21428/cb6ab371.8f91c230 ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com. Description: This video explores the complex reality of "bounded engagement" and how formerly incarcerated adults navigate formal institutions like banks, healthcare, and the labor market. Based on a 2026 study by Denver, Navarro, and Brunson involving nearly 100 interviews, we discuss why non-engagement is often caused by administrative burdens rather than voluntary opting out. Key Topics Covered in This Video: • Bounded Engagement defined: How people engage with institutions when possible but find informal alternatives when barriers exist. • Institutional Interdependency: How a barrier in one area (like lacking a state ID) creates roadblocks in others (like getting a job or credit card). • Financial Exclusion: Why minimum balance requirements push people toward "second chance banking" apps like Chime and Cash App. • The "SSI Dilemma": How income restrictions on government benefits can discourage formal employment. • System Avoidance: Why fear of surveillance is usually limited to specific institutions, such as those related to wage garnishment for child support. • Healthcare Success: How policy changes in Massachusetts (MassHealth) have led to high medical engagement among returning citizens. Reference: Denver, M., Navarro, O., & Brunson, R. K. (2026). Bounded Engagement and Institutional Interdependency: Exploring Formerly Incarcerated Adults’ (Non)Engagement Experiences and Perceptions. Journal of Research in Crime and Delinquency. #Criminology #Reentry #SocialJustice #CriminalJusticeReform #Sociology #BoundedEngagement #AdministrativeBurden

The accelerated digitalization of corporate environments has reshaped the nature of organizational risk, multiplying both technical vulnerabilities and failures of due diligence that can lead to corporate criminal liability. This study develops a criminological model of...

This is an overview based on the article, "Science Under Scrutiny: Strengthening Criminal Justice Research through Transparency and Local Engagement" (https://doi.org/10.21428/cb6ab371.f827ad5d ). We create these "Crimversations" with the AI tool Google NotebookLM. While we strive for accuracy, an overview may not perfectly reflect the original article, a limitation common to both AI-generated and human-led podcasts. For definitive information, please refer directly to the article. Stay tuned for the launch of our new sites, https://crimconsortium.com and https://crimhub.com.

Miller v. Alabama and Montgomery v. Louisiana restricted states’ ability to impose life without parole for youth under age 18 (henceforth JLWOP). Since Miller, 46 pieces of legislation across 34 states and the District of Columbia have altered JLWOP sentencing policies. The ...

Despite their importance as a tool for criminal groups and their potential role in helping law enforcement combat organized crime, there is still a lack of studies on aftermarket compartments (AMC) as the main object of inquiry. This report aimed to change this by ...

Criminal justice research is unfolding in a moment of uncertainty: universities are facing political scrutiny, federal funding streams remain unstable, and public trust in science is increasingly fragile. At the same time, partnerships with local agencies highlight both the...