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Jurisprudence Brett Kavanaugh Is Trying to Walk Back "Kavanaugh Stops." Justice Brett Kavanaugh does not seem happy that his name has become synonymous with racist immigration enforcement. In September, the justice wrote that Hispanic residents' "apparent ethnicity" could be a "relevant factor" in federal agents' decision to stop them and demand proof of citizenship. Immigration and Customs Enforcement and Customs and Border Protection promptly seized upon his opinion as a license to stop any Hispanic person on the basis of race--often with excessive, even sadistic force --and detain them until they proved their lawful presence. Law professor Anil Kalhan termed these encounters "Kavanaugh stops," and the name swiftly caught on as evidence mounted that they had become standard practice across the country.

Modeling complex human behavior, such as voter decisions in national elections, is a long-standing challenge for computational social science. Traditional agent-based models (ABMs) are limited by oversimplified rules, while large-scale statistical models often lack interpretability. We introduce FlockVote, a novel framework that uses Large Language Models (LLMs) to build a "computational laboratory" of LLM agents for political simulation. Each agent is instantiated with a high-fidelity demographic profile and dynamic contextual information (e.g. candidate policies), enabling it to perform nuanced, generative reasoning to simulate a voting decision. We deploy this framework as a testbed on the 2024 U.S. Presidential Election, focusing on seven key swing states. Our simulation's macro-level results successfully replicate the real-world outcome, demonstrating the high fidelity of our "virtual society". The primary contribution is not only the prediction, but also the framework's utility as an interpretable research tool. FlockVote moves beyond black-box outputs, allowing researchers to probe agent-level rationale and analyze the stability and sensitivity of LLM-driven social simulations.

Recent memoirs by the Justices reveal how a new vision of restraint has led to radical outcomes. To understand how grudging Amy Coney Barrett's new book is when it comes to revealing personal details, consider that one of the family members the Supreme Court Justice most often refers to is a great-grandmother who died five years before she was born. On Barrett's desk at home, she recounts in " Listening to the Law," she keeps a photograph of her great-grandmother's one-story house, where, as a widow during the Great Depression, she raised some of her thirteen children and took in other needy relatives. "Looking at the photo reminds me of a woman who stretched herself beyond all reasonable capacity," Barrett explains. "I'm not sure that I'll be able to manage my life with the same grace that she had. But she motivates me to keep trying." For Barrett, the mother of seven children, that effort entails setting her alarm for 5 "Our kids get up at six thirty during the school year, so I start early if I want to accomplish anything on my own to-do list," she writes. This is what passes for disclosure from Barrett; she measures out the details of her life with coffee spoons, careful not to spill.

Despite its constitutional relevance, the technical ``individual fairness'' criterion has not been operationalized in U.S. state or federal statutes/regulations. We conduct a human subjects experiment to address this gap, evaluating which demographic features are relevant for individual fairness evaluation of recidivism risk assessment (RRA) tools. Our analyses conclude that the individual similarity function should consider age and sex, but it should ignore race.

Large language models (LLMs) are entering legal workflows, yet we lack a jurisdiction-specific framework to assess their baseline competence therein. We use India's public legal examinations as a transparent proxy. Our multi-year benchmark assembles objective screens from top national and state exams and evaluates open and frontier LLMs under real-world exam conditions. To probe beyond multiple-choice questions, we also include a lawyer-graded, paired-blinded study of long-form answers from the Supreme Court's Advocate-on-Record exam. This is, to our knowledge, the first exam-grounded, India-specific yardstick for LLM court-readiness released with datasets and protocols. Our work shows that while frontier systems consistently clear historical cutoffs and often match or exceed recent top-scorer bands on objective exams, none surpasses the human topper on long-form reasoning. Grader notes converge on three reliability failure modes: procedural or format compliance, authority or citation discipline, and forum-appropriate voice and structure. These findings delineate where LLMs can assist (checks, cross-statute consistency, statute and precedent lookups) and where human leadership remains essential: forum-specific drafting and filing, procedural and relief strategy, reconciling authorities and exceptions, and ethical, accountable judgment.

New Supreme Court term will reshape Trump's powers The US Supreme Court begins its new term on Monday with a docket already full of potentially significant cases that could define the scope of Donald Trump's presidential authority - and the prospect of more to come. In the eight months that Trump has been back in the White House, he has tested the limits of executive power, unilaterally implementing new policies, slashing federal budgets and workforce, and attempting to bring previously independent agencies and institutions more directly under his control. The latest brewing legal battle comes from the president's attempts to take control of state National Guard units and deploy them in cities where he claims there is public unrest and rampant crime - over the objection of local and state officials. In Oregon, a federal judge has issued orders blocking Trump's deployment of troops to Portland. An appeals court is set to review the move in the coming days.

Things to Do in L.A. Tap to enable a layout that focuses on the article. California has a strict vaccine mandate. Will it survive the Trump administration? Dr. Neville Anderson, right, tries to distract Perry Roj, 4, while nurse Breanna Kirby gives her a DTaP polio vaccination. Her mom, Devin Homsey, holds her tight at Larchmont Pediatrics.

This week, Emily Bazelon, John Dickerson, and David Plotz discuss whether the US should join Israel's war on Iran, the tragic Minnesota assassinations and why US political violence is surging now, and the Supreme Court's unsurprising but willfully obtuse decision to uphold Tennessee's youth transgender care ban. Here are some notes and references from this week's show: Alexander Ward, Lara Seligman, and Dustin Volz for The Wall Street Journal (Exclusive): Israel Built Its Case for War With Iran on New Intelligence. The U.S. Didn't Buy It. Thomas L. Friedman for The New York Times (Opinion): The Smart Way for Trump to End the Israel-Iran War Oren Cass for Understanding America (Substack): Is Israel the Ideal "America First" Ally? Warren P. Strobel, Alex Horton, and Abigail Hauslohner for the Washington Post: Navigating Iran crisis, Trump relies on experience over star power Amy Howe for SCOTUSblog: Court upholds Tennessee's ban on certain medical treatments for transgender minors Abbie VanSickle for The New York Times: Sotomayor Writes the Court'Abandons' Transgender Children to'Political Whims' Ella Lee for The Hill: Clarence Thomas urges courts to end deferring to'experts' on gender-affirming care Ian Millhiser for Vox: The Supreme Court's incoherent new attack on trans rights, explained Here are this week's chatters: Emily: A Family Matter by Claire Lynch; The Fall of Affirmative Action: Race, the Supreme Court, and the Future of Higher Education by Justin Driver; A Flower Traveled in My Blood: The Incredible True Story of the Grandmothers Who Fought to Find a Stolen Generation of Children by Haley Cohen Gilliland. John: Mary Cunningham for CBS News: Federal Reserve holds its benchmark interest rate steady at today's FOMC meeting; ABA Banking Journal: Fed's Powell says some areas of U.S. may be'uninsurable' in next decade David: Trip Gabriel for the New York Times: William Langewiesche, the'Steve McQueen of Journalism,' Dies at 70 For this week's Slate Plus bonus episode, Emily, John, and David discuss the exciting possibilities and likely limitations of using AI tools for historical research and writing.

Topic modeling in Italian legal research is hindered by the lack of public datasets, limiting the analysis of legal themes in Supreme Court judgments. To address this, we developed a document processing pipeline that produces an anonymized dataset optimized for topic modeling. The pipeline integrates document layout analysis (YOLOv8x), optical character recognition, and text anonymization. The DLA module achieved a mAP@50 of 0.964 and a mAP@50-95 of 0.800. The OCR detector reached a mAP@50-95 of 0.9022, and the text recognizer (TrOCR) obtained a character error rate of 0.0047 and a word error rate of 0.0248. Compared to OCR-only methods, our dataset improved topic modeling with a diversity score of 0.6198 and a coherence score of 0.6638. We applied BERTopic to extract topics and used large language models to generate labels and summaries. Outputs were evaluated against domain expert interpretations. Claude Sonnet 3.7 achieved a BERTScore F1 of 0.8119 for labeling and 0.9130 for summarization.