Court-reported competence to proceed data across the United States.

OBJECTIVE: Competence to proceed (CTP) is a constitutional protection intended to facilitate fairness and dignity of court proceedings. Researchers have estimated that between 60,000 and 94,000 defendants are evaluated for CTP each year. Yet no research has systematically identified the number of evaluations conducted each year, despite their critical role and many profound implications. We used large-scale, systematic data collection to address this knowledge gap. HYPOTHESES: Given the siloed nature of the judicial and forensic mental health systems, we anticipated incomplete data and that the number of evaluations would far exceed previous estimates. METHOD: In September 2019, we used public information requests to solicit CTP evaluation order data from the judiciaries of 50 U.S. states, the District of Columbia, and the Federal Bureau of Prisons. We accepted evaluation proxies, such as evaluations ordered or evaluations filed, from the 2018/2019 calendar/fiscal year. We used Uniform Crime Reporting data to estimate a nationwide evaluation-to-arrest ratio and annual evaluation volume. RESULTS: Twenty-five states provided data. We deemed data from 18 states acceptable while acknowledging that data likely underrepresented actual evaluation volume. By extrapolating data from these 18 states, we estimated a conservative national evaluation-to-arrest ratio of 0.015 (95% confidence interval [-0.007, 0.037]), which suggested that 15 evaluations are conducted per 1,000 arrests each year. Consequently, it seems likely that at least 140,000 evaluations are ordered each year nationwide, with several hundred people referred for evaluations each day. CONCLUSIONS: Annual CTP evaluation volume likely far exceeds previous estimates. Transparent data are difficult, if not impossible, to obtain. As a result, researchers, legal and forensic mental health professionals, and policymakers lack the ability to implement informed, constitutionally protected CTP practices. Key implications, research directions, and detailed data infrastructure recommendations are provided. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The forensic potential of environmental DNA (eDNA) in freshwater wildlife crime investigations: From research to application.

Environmental DNA (eDNA) is widely used in biodiversity, conservation, and ecological studies but despite its successes, similar approaches have not yet been regularly applied to assist in wildlife crime investigations. The purpose of this paper is to review current eDNA methods and assess their potential forensic application in freshwater environments considering collection, transport and persistence, analysis, and interpretation, while identifying additional research required to present eDNA evidence in court. An extensive review of the literature suggests that commonly used collection methods can be easily adapted for forensic frameworks providing they address the appropriate investigative questions and take into consideration the uniqueness of the target species, its habitat, and the requirements of the end user. The use of eDNA methods to inform conservationists, monitor biodiversity and impacts of climate change, and detect invasive species and pathogens shows confidence within the scientific community, making the acceptance of these methods by the criminal justice system highly possible. To contextualise the potential application of eDNA on forensic investigations, two test cases are explored involving i) species detection and ii) species localisation. Recommendations for future work within the forensic eDNA discipline include development of suitable standardised collection methods, considered collection strategies, forensically validated assays and publication of procedures and empirical research studies to support implementation within the legal system.

Effect of pachinko parlour openings and closings on neighbourhood income-generating crimes in Japan: 6.5 years of observations.

BACKGROUND: Electronic gambling machines (EGMs) in gambling venues cause gambling-related harm and are a public health concern. This study focused on pachinko parlours as gambling venues and income-generating crimes as gambling-related harm. We aimed to verify whether income-generating crime rates increase in proximity to pachinko parlours and during the opening and post-closing periods of pachinko parlours relative to the pre-opening periods. METHODS: We used crime records spanning 6.5 years, including data on the opening and closing days of pachinko parlours for 6.5 years. We also sampled the addresses of convenience stores, bowling alleys, and households with official land prices all over Japan. The dependent variable was the daily income-generating crime incidence rate. Areas within 0.5 km, 0.5-1 km, 1-5 km, and 5-10 km radii of the pachinko parlours were the independent variables. The pre-, opening-, and post-closing periods of the pachinko parlours were also independent variables. The covariates included the number of convenience stores and always open pachinko parlours near pachinko parlours. Data were analysed using an analysis of variance (ANOVA) and covariance (ANCOVA). We also used differences-in-differences analysis (DD) to reveal the increase in income-generating crime rates in neighbourhoods exposed to the opening or closing of pachinko parlours. RESULTS: The daily income-generating crime incidence rate was significantly higher in areas within 0.5-1 km and 1-5 km radii of pachinko parlours than in those within 0.5 km and 5-10 km radii of them. The daily income-generating crime incidence rate was also significantly higher during the opening and post-closing periods than during the pre-opening period, even when controlling for the number of convenience stores and always open pachinko parlours. In particular, fraud crime rates increased with the opening and closing of pachinko parlours. CONCLUSIONS: The highest income-generating crime incidence rate was observed within a 0.5-1 km and 1-5 km radius of pachinko parlours. The opening of pachinko parlours also increased income-generating crime incidence rates, which increased after closing. Pachinko parlours are considered to be creating public harm because the corporate activities of these parlours make the youth in their neighbourhood perpetrators of fraud and older adults its victims. Future research should examine the current findings using official crime records.

The Role of Engineering Ethics in Mitigating Corruption in Infrastructure Systems Delivery.

Indications that corruption mitigation in infrastructure systems delivery can be effective are found in the literature. However, there is an untapped opportunity to further enhance the efficacy of existing corruption mitigation strategies by placing them explicitly within the larger context of engineering ethics, and relevant policy statements, guidelines, codes and manuals published by international organizations. An effective matching of these formal statements on ethics to infrastructure systems delivery facilitates the identification of potential corruption hotspots and thus help establish or strengthen institutional mechanisms that address corruption. This paper reviews professional codes of ethics, and relevant literature on corruption mitigation in the context of civil engineering infrastructure development, as a platform for building a structure that connects ethical tenets and the mitigation strategies. The paper assesses corruption mitigation strategies against the background of the fundamental canons of practice in civil engineering ethical codes. As such, the paper's assessment is grounded in the civil engineer's ethical responsibilities (to society, the profession, and peers) and principles (such as safety, health, welfare, respect, and honesty) that are common to professional codes of ethics in engineering practice. Addressing corruption in infrastructure development continues to be imperative for national economic and social development, and such exigency is underscored by the sheer scale of investments in infrastructure development in any country and the billions of dollars lost annually through corruption and fraud.

Abnormal Behavior Recognition Based on 3D Dense Connections.

Abnormal behavior recognition is an important technology used to detect and identify activities or events that deviate from normal behavior patterns. It has wide applications in various fields such as network security, financial fraud detection, and video surveillance. In recent years, Deep Convolution Networks (ConvNets) have been widely applied in abnormal behavior recognition algorithms and have achieved significant results. However, existing abnormal behavior detection algorithms mainly focus on improving the accuracy of the algorithms and have not explored the real-time nature of abnormal behavior recognition. This is crucial to quickly identify abnormal behavior in public places and improve urban public safety. Therefore, this paper proposes an abnormal behavior recognition algorithm based on three-dimensional (3D) dense connections. The proposed algorithm uses a multi-instance learning strategy to classify various types of abnormal behaviors, and employs dense connection modules and soft-threshold attention mechanisms to reduce the model's parameter count and enhance network computational efficiency. Finally, redundant information in the sequence is reduced by attention allocation to mitigate its negative impact on recognition results. Experimental verification shows that our method achieves a recognition accuracy of 95.61% on the UCF-crime dataset. Comparative experiments demonstrate that our model has strong performance in terms of recognition accuracy and speed.

Parents' 'fault' must not weigh on their children. Surrogacy as a universal crime in Italy: Is it compatible with bioethical principles?

Abstract: Assisted reproduction techniques (ARTs) have given rise to novel, non-traditional family models. Still, among the various applications and approaches of 'medically assisted procreation' (MAP), the most divisive one undoubtedly is 'gestational surrogacy' (GS), also in light of the rising number of couples who have chosen it over the past twenty years. Another major implication of ARTs is the creation of intentional (or intended) parenthood in addition to genetic one: the genetic parent's partner is thus defined as the intentional (or second) parent, who by free choice, shares the family project with the genetic parent, even without any biological tie with the child. Hence, the intended parent takes on the same rights and responsibilities towards the child as the biological one. Several countries, including Italy, have enacted norms to discourage cross-border surrogacy, deeming it harmful to the dignity of women and children. Recently, however, the Italian government has decided intensify the fight against this practice: the Chamber of Deputies (Italy's lower chamber of parliament) has passed a law which punishes couples that resort to surrogacy even if the agreement and the birth take place abroad. Therefore, surrogacy would become a so-called universal crime. In light of the fact that criminalization is a serious and highly consequential step, which may have life-changing consequences for the intended parents, the aim of this paper is to assess whether this may be an effective instrument for regulating the interests at stake and, therefore, whether it would be desirable for other countries to follow such a model. Ultimately, it is worth remarking that for those who seek to achieve parenthood, such a desire is among the most profound aspects of a person's existential realization. When due to a delicate balance of ethics standards and potentially conflicting rights, lawmakers inter-vene, an authoritarian approach is unlikely to be beneficial. Offering real alternatives to surrogacy in an organic and pragmatic fashion (i.e. expediting adoption procedures, favoring motherhood at a younger age, when infertility issues are less likely to have set in) may be the best way to disincentivize fertility traveling and make sure the rights, hopes and aspirations of all the parties involved are upheld properly.

The role of corruption in global food systems: a systematic scoping review.

BACKGROUND: Corruption exists at all levels of our global society and is a potential threat to food security, food safety, equity, and social justice. However, there is a knowledge gap in the role and impact of corruption within the context of the global food system. We aimed to systematically review empirical literature focused on corruption in the global food system to examine how it is characterized, the actors involved, its potential impacts, and the solutions that have been proposed to address corruption in the food system. METHODS: We used a systematic scoping review methodology. Terms combining corruption and the food system were searched in Scopus, PubMed, Web of Science, PsycInfo and Econlit, in October 2021. Two screeners applied a priori selection criteria to screen the articles at the title and abstract and full-text levels. Data was extracted into a charting form and thematically synthesized to describe the types of corruption in the food system, the actors involved, how corruption impacts the food system, and potential solutions. Sankey diagrams and narrative summaries were developed to summarize the included studies and findings. RESULTS: From the 238 included records, five main types of corruption were identified in the global food system: bureaucratic corruption, fraud, bribery, organized crime, and corporate political activity. These different types of corruption spanned across various food system areas, from policy and governance structures to food environments, and involved a wide range of actors. More powerful actors like those in public and private sectors tended to instigate corruption in the food system, while community members and primary producers tended to be impacted by it. The impacts of corruption were mostly negative and corruption was found to undermine food system governance and regulatory structures; threaten health, safety, and food security; and lead or contribute to environmental degradation, economic loss, erosion of trust, social inequities, and decreased agricultural productivity. While solution-oriented literature was limited, the essential role of strong governance,  use of technology and predictive modelling methods to improve detection of corruption, and organizational approaches to problem solving were identified. CONCLUSION: Our review findings provide researchers and policymakers with a comprehensive overview of corruption in the global food system, providing insights to inform a more holistic approach to addressing the issue. Addressing corruption in the food system is an essential element of supporting the transition to a more healthy, equitable and sustainable global food system.

Gentrification and crime in Buffalo, New York.

Since the 1990s, gentrification has significantly changed American urban landscapes. Its implications for crime are under recent scrutiny, particularly in large cities like New York City, Los Angeles, and Chicago. We extend this literature by focusing on the gentrification-crime link in the midsize city of Buffalo, New York using nine years of data from the American Community Survey and the Buffalo Police Department. Examining changes both within tracts over time and changes between gentrified and never-gentrified tracts, we find that gentrification is associated with reduced property crime and is not associated with changes in violent crime. More specifically, in comparing crime trends across tracts, we find that gentrified tracts show a trajectory of declining property crime that mirrors more advantaged tracts, while vulnerable-but-never-gentrified tracts show a U-shaped trajectory of property crime. Looking at within-tract changes, we find that years following gentrification of a given tract have lower property crime rates than years preceding gentrification, independent of the general reduction in crime over time. We discuss the implications of these findings for understanding the intersections between urban processes and crime.

Economic barriers to prevent the smuggling of health goods in Iran.

INTRODUCTION: In recent years, smuggling of health goods has apparently increased in the country. Despite the preventive and regulatory measures taken to combat this problem, the outcomes seem to be undesirable. This study thus aims to identify and elucidate the role of economic barriers in the prevention of smuggling health goods in Iran. METHOD: We conducted semistructured interviews with 29 purposefully identified key informants in the detection, prevention and control of health goods smuggling in different organisations, between May 2021-January 2022. An inductive data-driven thematic analysis approach was further adopted to identify patterns of meaning, using MAXQDA 2020 software to facilitate data management. RESULTS: We identified four main themes representing the economic barriers to prevent the smuggling of health goods in Iran; Monetary and financial policy, which includes subthemes of financial rules and procedures, market regulation, economic incentives and imbalanced development; Behavioural patterns, consisting of consumer behaviour, the opportunism of smugglers, the behaviour of statesmen and politicians; Economic diplomacy, categorised into international relations and interactions, relations and interactions in the national arena, interaction with non-governmental organisations and Health economic monitoring and evaluation including transparency of statistics and economic information and supervision. CONCLUSION: Smuggling health goods has become a concerning challenge in the health sector. It is, therefore, imperative to develop and implement appropriate policies and operations towards security and international cooperation, lobbying and coalition-building. Demonopolisation, creating competitive and dynamic markets, removal of rent-seeking layers at all levels, and the use of commercial diplomacy to reduce the burden of smuggling in the health sector of Iran, and perhaps beyond might be of sizeable use to combat such challenge.

Do digital technologies reduce racially biased reporting? Evidence from NYPD administrative data.

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department's replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of "unproductive" stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

Examining the Past Injustices Suffered by Those in Corrections and the General Public: A New Therapeutic Approach May Be Necessary.

One under-researched area within corrections is the connection among (a) past adverse events, particularly in the form of injustices against those who now are incarcerated, (b) crimes committed and then (c) healing from the effects of that past adversity of injustice. Might those who have experienced severe injustices against them develop an anger or a hatred that then is displaced onto others, leading to arrest, conviction and imprisonment? This is not to imply that societies condone illegal behaviour but instead to assist in the healing from the adversity so that future crime is reduced. As a first step in this sequence, the study here examined in detail the kinds of injustices suffered by men in a maximum-security correctional institution (N = 103) compared with men in a medium-security environment (N = 37) and in the general public (N = 96). Findings indicated differences between those in the general public and those in the two correctional contexts. The latter two groups had (a) a higher severity of injustices against them (rated by a panel of researchers), (b) a more negative current impact that past injustices are having on them (also rated by a panel of researchers), (c) more reports that the injustices contributed to their choices to harm others, (d) more serious types of hurt (such as sexual abuse), (e) a stronger degree of self-reported hurt and (f) more injustices from family members. Implications for correctional rehabilitation to reduce the negative psychological effects caused by the injustices of others are discussed.

Witnessing-condition information differentially affects evaluations of high- and moderate-confidence eyewitness identifications.

Recent research on the eyewitness confidence-accuracy relationship reveals that confidence can be highly diagnostic of accuracy when the identification evidence is collected using pristine procedures (Wixted & Wells, 2017) and in the absence of suspect bias (Smalarz, 2021). Some researchers have further argued that eyewitnesses who make high-confidence suspect identifications are highly likely to be accurate even if they experienced suboptimal witnessing conditions (Semmler et al., 2018). The current research examined evaluations of eyewitness identification evidence in cases involving suboptimal witnessing conditions. Students (Experiments 1 & 2) and community members (Experiment 3) read eight crime vignettes involving an eyewitness's identification. We manipulated information about poor witnessing conditions (present vs. absent), the eyewitness's confidence level (high vs. moderate), and the format of the confidence statement (verbal vs. numeric) and measured evaluations of eyewitness-identification accuracy. Across all three experiments, information about suboptimal witnessing conditions disproportionately reduced evaluators' belief of highly confident compared to moderately confident eyewitnesses. This differential-discrediting pattern occurred for both numeric and verbal confidence-statement formats. Expert testimony describing the imperviousness of high-confidence suspect-identification accuracy to suboptimal witnessing conditions reduced, but did not eliminate, the differential-discrediting effect. Given that crime eyewitnesses frequently experience suboptimal witnessing conditions (e.g., Behrman & Davey, 2001; Wright & McDaid, 1996), the current findings have widespread implications for the capacity of the legal system to correctly classify suspects as guilty or innocent based on eyewitness identification testimony.

The perceived guilt and innocence of adults with developmental language disorder and adults with typical language during a mock interrogation.

PURPOSE: This study examined if there were differences in the guilty and not guilty judgments of adults with developmental language disorder (DLD) and those with typical language (TL) functioning. METHOD: Twenty-four adults (12 DLD, 12 TL) were assigned to either the guilty or not guilty conditions. Those in the guilty condition engaged in a mock crime while those in the not guilty condition were informed that a crime had been committed. Peer jurors were presented with video interrogations of the DLD (6 guilty, 6 not guilty) and TL (6 guilty, 6 not guilty) participants and were asked to make categorical judgments of guilty and not guilty and to indicate confidence in their judgments. RESULTS: In general, peer jurors were not accurate in their judgments of the accused, and were more likely to judge individuals with DLD as guilty relative to accused individuals with TL. Peer jurors were particularly poor at judging innocent adults with DLD as not guilty and guilty adults with TL as guilty. Despite this, peer jurors were more confident than not in their guilty and not guilty determinations. CONCLUSIONS: Peer jurors are confident in their judgments of the guilt of the accused when they should not be, particularly in the case of accused adults with DLD. Implications are discussed.

Maximal fines and corruption: An experimental study on illegal waste disposal.

Corruption is known to be one of the real life situations which may jeopardize the effectiveness of fines in deterring crime. We present a model of 'crime with corruption' by which both the dilution of crime deterrence due to corruption, as well as the possibility of crime encouraging fines, are formally highlighted. More importantly, by running an experiment on a subject pool of students for the case of illegal waste disposal, we provide experimental evidence on the validity of our theoretical predictions. We find that increasing fine rate may become crime encouraging, or at least ineffective, beyond a context-specific fine threshold. From a policy perspective, we suggest that the optimal design of a crime-deterring sanctioning system must simultaneously account for both corruption practices and anti-corruption policies.

On the advantages of using AI-generated images of filler faces for creating fair lineups.

Recent advances in artificial intelligence (AI) enable the generation of realistic facial images that can be used in police lineups. The use of AI image generation offers pragmatic advantages in that it allows practitioners to generate filler images directly from the description of the culprit using text-to-image generation, avoids the violation of identity rights of natural persons who are not suspects and eliminates the constraints of being bound to a database with a limited set of photographs. However, the risk exists that using AI-generated filler images provokes more biased selection of the suspect if eyewitnesses are able to distinguish AI-generated filler images from the photograph of the suspect's face. Using a model-based analysis, we compared biased suspect selection directly between lineups with AI-generated filler images and lineups with database-derived filler photographs. The results show that the lineups with AI-generated filler images were perfectly fair and, in fact, led to less biased suspect selection than the lineups with database-derived filler photographs used in previous experiments. These results are encouraging with regard to the potential of AI image generation for constructing fair lineups which should inspire more systematic research on the feasibility of adopting AI technology in forensic settings.

Risk factors for dropout from psychological substance use disorder treatment programs in criminal justice settings.

BACKGROUND: Substance use disorders are highly prevalent in people within the criminal justice system. Psychological programs are the most common type of treatment available and have been shown to decrease recidivism, but dropping out of treatment is common. Risk factors associated with treatment dropout remain unclear in this setting, and whether the risk factors differ by treatment form (group-based vs. individual). METHODS: Outcome (treatment dropout) was defined as not finishing the program due to client's own wish, misbehavior, no-shows, or because program leader found client to be unsuitable. Predictors of treatment dropout included a comprehensive set of individual-level clinical, socioeconomic, and crime-related pre-treatment characteristics. Multivariable regression models were used to estimate the associations between predictors and dropout. FINDINGS: The study cohort included 5239 criminal justice clients who participated in a psychological treatment program (group-based or individual). Multivariable logistic regression models showed that female sex (OR=1.64, 95% CI 1.20-2.25), age (0.99, [0.97-1.00]), sentence length (0.98, [0.97-0.98]), higher education (0.54, [0.28-1.00]), number of violent offenses (1.03, [1.01-1.05]), and anxiety disorders (1.32, [1.01-1.72]) were associated with dropout from the individual treatment program. For the group-based program, age (OR=0.98, 95% CI 0.96-1.00), sentence length (OR=0.96, 95% CI 0.94-0.98), stimulant use disorder (OR=1.48, 95%, 1.00-2.19), and self-harm (OR 1.52, 95% CI 1.00-2.34) were associated with dropout. CONCLUSIONS: We identified certain sociodemographic, crime-related, and clinical characteristics that were particularly important in predicting dropout from psychological treatment. Further, we find that there are similarities and differences in predictors of dropout from group-based and individual treatment forms.

Characteristics of background check findings in nursing students.

BACKGROUND: Background checks are used in nursing education to assess public risk. To date, no study has described the most common and most serious findings in nursing students. PURPOSE: Our study describes the most common and most serious characteristics of BGC findings in nursing students attending large universities. METHOD: Our retrospective study describes characteristics of aggregated, de-identified background check data from a convenience sample of 16 US nursing programs set in large universities 2014-2019. FINDINGS: Sampled programs collected 45,613 background checks, with 1548 findings (3.4 %). Severity of findings included criminal (62.5 %), non-criminal (4.6 %), felony (0.8 %), and other (11.6 %). Severity data were missing from 20.4 % of records. Finding types included substance use (23.7 %), disorderly conduct (8.7 %), property crimes (2.4 %) and crimes against persons (1 %). Type data was missing from 64.3 % of records. DISCUSSION: Future research should examine whether background check type or severity indicates a nursing student poses a public risk.