A Quantitative Study on Restorative Justice Programs and Socioeconomic Status on Gun Violence Prevention in Urban Schools

A gun violence epidemic had been a topic of conversation in America\u27s schools in the form of mass shootings, homicides, nonfatal attacks, accidental discharges, and weapon suicides. The significance of this issue lies in its effects on student safety, well-being, and educational outcomes. A logistic regression model was used to assess the impact of free or reduced-price lunch (SES) and the adoption of restorative justice practices on the likelihood of firearm incidents in schools. Using social learning theory and trauma-informed care, this quantitative study used surveys from 7,290 individuals to analyze these correlations. The findings revealed significant reductions in gun-related incidents in schools that implement restorative justice strategies, especially in those with higher numbers of low-income students. Restorative justice strategies effectively addressed behavioral issues and contribute to a supportive school climate, which enhances emotional well-being. Human services professionals are essential in the implementation of restorative justice practices, and policy reforms should incorporate restorative justice into school disciplinary frameworks, moving away from zero-tolerance policies. Social change implications include support for restorative justice practices and their potential impact. Promoting restorative justice can lead to safer and more equitable learning environments, addressing social determinants of health and enhancing student well-being. Further research is recommended on the application of restorative justice practices in diverse school settings and their long-term effects

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe