Empiricism and the Misdemeanor Courts: Promoting Wider, Deeper, and Interdisciplinary Study

Since 1956, there have been three waves of scholarly attention on the misdemeanor courts. Despite this attention, misdemeanor courts remain understudied and overlooked. The object of this paper is to summarize the empirical research conducted over the last sixty years and identify the scholarly work that should be undertaken on the processing of misdemeanor offenders in our courts. Buoyed by the current interest in studying the misdemeanor courts, scholars should widen and deepen their study by replicating the work of others in a variety of jurisdictions, observing court proceedings, interviewing defendants and the courtroom workgroup, and assessing whether constitutional ideals are being upheld by our misdemeanor courts

Cultural Issues

This Grants Collection uses the grant-supported open course ESED 5234 from Georgia Southern University: http://digitalcommons.georgiasouthern.edu/esed5234-master/ This Grants Collection for Cultural Issues was created under a Round Four ALG Textbook Transformation Grant. Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process. Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials: Linked Syllabus Initial Proposal Final Reporthttps://oer.galileo.usg.edu/education-collections/1005/thumbnail.jp

In Honor of Walter O. Weyrauch: The Case for Overturning Williams v. Florida and the Six-Person Jury: History, Law, and Empirical Evidence

After 700 years of common-law history and nearly 200 years of constitutional history, the Supreme Court concluded that the constitutionally permissible minimum jury size could not be inferred from the language or the history of the Constitution. The answer, said the Court in Williams v. Florida, could be found only through a “functional analysis” of the performance of smaller juries (that is, empirical examination of the behavior of different-sized juries). The Court implicitly abandoned that analysis in Ballew v. Georgia, when it held that juries with fewer than six members were unconstitutional-a decision based on nothing more than the ipse dixit of the Justices. This Essay sets out the historical and empirical infirmities of the Williams line of cases. It summarizes the jury sizes required in criminal prosecutions throughout the United States; examines the Sixth Amendment history of the jury trial; argues that this history supports the position that the Constitution intended twelve-person juries; reviews Florida’s jury trial history; and summarizes the empirical research undertaken since Williams. This Essay concludes that at present no sound basis exists in law for knowing the minimum size of a constitutionally permissible jury. Williams, having become a dead letter in Ballew, should either be ratified (and the theory of functional equivalence applied conscientiously) or be formally reversed to allow courts either to develop a sound theory of the constitutionality of jury size or to restore the jury to its traditional size

How Language Model Hallucinations Can Snowball

A major risk of using language models in practical applications is their tendency to hallucinate incorrect statements. Hallucinations are often attributed to knowledge gaps in LMs, but we hypothesize that in some cases, when justifying previously generated hallucinations, LMs output false claims that they can separately recognize as incorrect. We construct three question-answering datasets where ChatGPT and GPT-4 often state an incorrect answer and offer an explanation with at least one incorrect claim. Crucially, we find that ChatGPT and GPT-4 can identify 67% and 87% of their own mistakes, respectively. We refer to this phenomenon as hallucination snowballing: an LM over-commits to early mistakes, leading to more mistakes that it otherwise would not make

That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?

The translation of ambiguous text presents a challenge for translation systems, as it requires using the surrounding context to disambiguate the intended meaning as much as possible. While prior work has studied ambiguities that result from different grammatical features of the source and target language, we study semantic ambiguities that exist in the source (English in this work) itself. In particular, we focus on idioms that are open to both literal and figurative interpretations (e.g., goose egg), and collect TIDE, a dataset of 512 pairs of English sentences containing idioms with disambiguating context such that one is literal (it laid a goose egg) and another is figurative (they scored a goose egg, as in a score of zero). In experiments, we compare MT-specific models and language models for (i) their preference when given an ambiguous subsentence, (ii) their sensitivity to disambiguating context, and (iii) the performance disparity between figurative and literal source sentences. We find that current MT models consistently translate English idioms literally, even when the context suggests a figurative interpretation. On the other hand, LMs are far more context-aware, although there remain disparities across target languages. Our findings underline the potential of LMs as a strong backbone for context-aware translation.Comment: EMNLP 2023 Finding