St. Edward's University

The gay and trans panic defense is a long-standing legal strategy that "heterosexual" men have employed in criminal courtrooms to excuse or justify lethal violence against gay men or transgender women. While studies have investigated this defense for 35 years, research has yet to analyze a large sample of gay and trans panic defense court outcomes. This study addresses this gap by conducting a descriptive and bivariate analysis of 587 defendants who raised panic defenses in homicide cases within the United States from 1970 to 2023. Specifically, this work analyzed the gay and trans panic defense, as well as individual, situational, and legal variables, across four criminal court outcomes: dismissal of charges versus prosecution, plea bargain versus continue to trial, acquittal versus conviction, and leniency versus conviction on the original charge(s). Drawing on research on homicide case processing and focal concerns theory, this work explores whether court outcomes align with variables suggestive of defendant/victim culpability. This study found no statistical association between lenient court convictions and victim gender. However, bivariate analysis found that lenient convictions were associated with defendants who negotiated plea bargains, raised self-defense claims for trial, and utilized legal counsel who criminalized the victim's sexual orientation or gender.

Household wealth from the stock market is unevenly concentrated among higher-income groups, and its distribution may be affected by stock market volatility. This paper investigates the relationship between stock market volatility and consumer spending through the lens of wealth distribution, with particular attention to different monetary policy environments. Using quarterly U.S. data from 1989 to 2024 within a state-dependent econometric framework, the study finds that stock market volatility significantly increases wealth inequality and lowers real per capita spending on durable goods, nondurable goods, and services during periods of easy monetary policy. Conversely, no significant effects are found under tight monetary policy, highlighting the state-dependent nature of the volatility-consumption relationship. This state dependency indicates a nonlinear dynamic relationship between stock market volatility and consumer spending. Additionally, results show that stock market volatility has a temporary effect on economic uncertainty and a smaller impact on consumption behavior than consumer sentiment. Policy recommendations include stabilization of stock market volatility and implementing confidence-building measures to sustain consumer spending and promote steady economic growth.

Risk assessment tools are used in criminal justice to evaluate an individual’s likelihood of reoffending. There is a growing discussion around the use of artificial intelligence (AI) and machine learning (ML) in algorithmic risk assessment (ARA). This survey examines the use of and the potential for bias in the use of ARA in criminal justice. Through a structured interdisciplinary review of recent research on the impact of ARA, this investigation examines the tools currently being used and whether there is evidence that ARA tools contribute to bias. Included papers were collected from Google Scholar and the ACM Digital Library and have been published since 2015, discuss AI, and focus on the adult justice system in the US, yielding 56 studies. In total, 79% of the surveyed literature concluded that AI and ML can or do contribute to biased performance in risk assessment. The two most recorded sources of bias were the use of historical court records as training data and the use of variables or features that correlate strongly with race, gender, age, or other protected attributes, while noting that this result relies heavily on a small number of real-world observations, most notably the COMPAS dataset collected in Broward County. The recorded benefits of ARA included efficiency and resource utilization. The use of AI-derived risk assessment tools is growing and holds the potential to affect a lot of lives. It is important to examine and consider the implications of their use, especially involving bias and fairness in criminal justice decision-making.

Salmonella in gut habitats have traditionally been thought to conserve energy for growth via fermentation. However, recent reports indicate that ingested Salmonella can stimulate host-derived nitrate accumulation in the mucosal microenvironment, thereby enabling growth through nitrate respiration. Sodium tungstate is an effective treatment that inhibits the growth of certain nitrate-respiring bacteria, including Escherichia coli, Paracoccus and Proteus, when cultured under gut simulating conditions or within the gut of experimentally treated mice. This inhibitory effect is hypothesized to occur by inactivation of molybdenum-containing enzymes required for nitrate metabolism. Information is lacking on whether tungstate can inhibit the growth of Salmonella, particularly in the presence of culturable gut microbiota. Therefore, the objectives of this study were to evaluate the effects of sodium tungstate on Salmonella during pure culture or when cultured with freshly collected bovine rumen microbiota and to assess its impact on fermentation as well as nitrate and nitrite metabolism within the rumen microbial cultures. Our results indicate that 50 mM sodium tungstate treatment, whether alone or in combination with 5 mM nitrate, markedly increased the growth of Salmonella serovars Newport, Dublin and Typhimurium during pure culture. Moreover, during in vitro incubation, increased growth of experimentally inoculated S. Newport as well as wildtype E. coli and lactic acid bacteria was observed with ruminal microbiota treated with 100 mM tungstate when compared to non-tungstate-treated controls. Effects of tungstate on nitrate and nitrite metabolism were as expected during pure and mixed culture. When cultured with reduced tungsten rather than tungstate, the latter being bound to four oxygen atoms, an inhibitory effect on the growth of S. Newport was observed and effects on nitrate and nitrite metabolism were consistent with those observed with tungstate. These results suggest that, under conditions used in the present experiments, tungstate may have served as a source of oxygen for respiration above that achieved with nitrate alone. While this hypothesis has yet to be proven, it is supported by an adverse effect of tungstate, whether alone or in combination with 5 mM nitrate, on methane and volatile fatty acid production by the ruminal microbiota when compared to untreated or nitrate-only-treated microbiota.

The majority of work on summarization evaluation focuses on general summary quality (e.g., ROUGE, BERTScore) or specific desired properties (e.g., readability, factuality). However, these metrics fail to measure the utility of a summary to an individual user. For example, a biomedical researcher learning about the latest vaccine research will have different informational needs from a family doctor. Query-focused summarization captures part of this need, but in practice, users rarely state everything relevant in a query: a single short query is likely inadequate to distinguish the needs of a researcher from those of a physician. By contrast, a reader's background or persona (their role and expertise) is comparatively stable across queries and recovers much of this missing context, which makes it a practical signal for assessing whether a summary satisfies that reader's needs. In this work, we assess how sensitive popular summarization metrics are to both informational and persona differences, and find that many popular metrics, including strong LLM-as-judge metrics, fail basic perturbation tests of informational content. We additionally conduct an expert human evaluation, measuring summary preferences based on information satisfaction given a specific person's background and use case. We find that both traditional and LLM-based metrics are insufficient measures of information satisfaction and agree poorly with human judgment.