False Confessions in the American Justice System

False confessions occur when someone confesses to a crime they did not commit. These confessions can be voluntary, coerced-compliant, or coerced-internalized. This research focuses on the latter two types of false confessions. RESEARCH QUESTION: What causes false confessions, and what can be done to reduce their frequency and impact on court cases? METHODS: Research was conducted by finding, analyzing, and synthesizing primary and secondary sources. Sources were gathered from research journals and credible news sources. RESULTS: False confessions are detrimental not only to the lives of individuals, but also to our society. False confessions are frequently caused by faulty interrogation methods. We must work to reduce the number of false confessions by imposing restrictions on interrogation length and methods, as well as filming interrogations.https://digitalcommons.usu.edu/fsrs2022/1067/thumbnail.jp

Declining student enrollment in Virginia 1972-1981 : an examination of its extent, State Board of Education policies, and changes effected by selected school divisions

The purposes of the study were to determine: to what extent student enrollment has declined in the state and in local school divisions in Virginia during the decade 1972-1981; what policies, if any, have been enacted by the State Board of Education relative to declining enrollment; and what effect a severely declining enrollment may have had in the areas of formal curriculum, professional personnel, and school organizational patterns and utilization of buildings.;It was found that during the decade studied: (1) statewide enrollment declined overall by less than six percent; (2) 62 percent of the divisions experienced a net loss in enrollment; (3) nine divisions declined in enrollment for ten consecutive years; (4) eighteen divisions declined 20 percent and more; (5) eleven divisions declined by 25 percent and more.;No policies related to declining enrollment were enacted by the State Board of Education during the decade studied.;A questionnaire was sent to the superintendents of eleven divisions which had declined by 25 percent and more during the decade studied. Completed questionnaires were returned by ten divisions, or 91 percent. Changes related to declining enrollment were found to have been effected in the areas of formal curriculum, professional personnel, and school organizational patterns and utilization of buildings. While the respondents did not cite declining enrollment as the sole cause of the changes effected, 73 percent of the changes were reported to have been partially or substantially the result of declining enrollment. The eleven divisions studied included large cities, small cities, suburban, and rural areas within Virginia, and were geographically dispersed. Ninety percent of the responding divisions reported layoffs, involuntary transfers between schools, and establishment of new attendance zones. One hundred percent of the respondents cited seniority as either the only criterion or one of several criteria considered in their divisional reduction-in-force policy. None of the responding divisions were reported to have a School Board policy on the use of surplus space

Critical computation: mixed-methods approaches to big language data analysis

In this theoretical piece, we discuss the limitations of using purely computational techniques to study big language data produced by people online. Instead, we advocate for mixed-method approaches that are able to more critically evaluate and consider the individual and social impact of this data. We propose one approach that combines qualitative, traditional quantitative, and computational methods for the study of language and text. Such approaches leverage the speed and expediency of computational tools while also highlighting the value of qualitative methods in critically assessing the outcome of computational results. In addition to this, we highlight two considerations for communication scholars utilizing big data: (1) the need to consider more language variations and (2) the importance of self-reflexivity when conducting big language data research. We conclude with additional recommendations for researchers seeking to adopt this framework in the context of their own research