F22RS SGB No. 18 (Bike Repair Stations)

A bill to appropriate $15,500 from the Student Government Initiatives Account to fund the purchase of six (6) Bicycle Repair “Fixit” station

Strategies Utilized by Speech-Language Pathologists when Treating Speech-Language Disorders in Children who are Bilingual

In the state of Minnesota, more children who use a language other than English were reported to speak English less than “very well” (U.S. Census Bureau, 2020). There was neither a “gold standard” (Verdon, McLeod, & Wong, 2013), nor Preferred Practices (ASHA, 2020) for the treatment of speech-language disorders for children who were bilingual. The current study investigated the practices for treating speech-language disorders in this population by SLPs employed in schools in a region of west-central MN and eastern ND. Using an interpreter, and explicit instruction on targeted language skills were the most common clinical approaches utilized. The child’s relative proficiency in his/her languages was by far the most impactful factor in selecting the treatment language, yet most SLPs only used their L1 during interventions. Using the same treatment strategies as for monolingual children was the most commonly shared strategy, yet using interpreters and collaborating with the ELL teacher were the most commonly shared facilitators for treating this population. The most common barrier was a general lack of reliable access to bilingual support personnel. Overall, participants felt their training did not prepare them well for treating speech-language disorders in this population. Clinical implications related to the importance of educating SLPs and developing a base of research in intervention strategies for speech-language disorders for children who were bilingual

Harnessing GPT-3.5-turbo for Rhetorical Role Prediction in Legal Cases

We propose a comprehensive study of one-stage elicitation techniques for querying a large pre-trained generative transformer (GPT-3.5-turbo) in the rhetorical role prediction task of legal cases. This task is known as requiring textual context to be addressed. Our study explores strategies such as zero-few shots, task specification with definitions and clarification of annotation ambiguities, textual context and reasoning with general prompts and specific questions. We show that the number of examples, the definition of labels, the presentation of the (labelled) textual context and specific questions about this context have a positive influence on the performance of the model. Given non-equivalent test set configurations, we observed that prompting with a few labelled examples from direct context can lead the model to a better performance than a supervised fined-tuned multi-class classifier based on the BERT encoder (weighted F1 score of = 72%). But there is still a gap to reach the performance of the best systems = 86%) in the LegalEval 2023 task which, on the other hand, require dedicated resources, architectures and training

F22RS SGR No. 1 (Allen Hall Murals)

To Urge and Request Louisiana State University paint a new representation of Student Life over the Mural in Allen Hall depicting segregation and people of color picking cotto

Exploitation de lexiques pour la catégorisation fine d'émotions, de sentiments et d'opinions

International audienceNous présentons dans cet article notre proposition pour la 11 ème édition du Défi Fouille de Textes (DEFT). Nous participons à trois tâches proposées dans le cadre de cet atelier en fouille d'opinion. Les objectifs de ces tâches sont de classer des tweets en français sur le sujet des énergies renouvelables, respectivement du point de vue de la polarité, du type général d'information énoncé, et enfin de la classe fine du sentiment, de l'émotion ou de l'opinion exprimée. Pour réaliser cette catégorisation, nous proposons d'explorer et d'évaluer différentes méthodes de construction de lexiques typés sémantiquement : outre des lexiques affectifs construits manuellement, nous expérimentons des lexiques typés construits semi-automatiquement sur le corpus d'évaluation et d'autres sur un corpus tiers

Anti-atheist Discrimination, Outness, and Psychological Distress among Atheists of Color

Using a Concealable Stigmatized Identity (CSI) framework, the present study explored disclosure and concealment of atheist identity, anti-atheist discrimination, and psychological distress among participants (N = 87) identified as both atheists and people of color residing in the United States (US). Path analysis was utilized to examine the relationships among variables. Consistent with past CSI and outness research, the final model suggested small, significant associations between higher disclosure of atheist identity and more experiences of anti-atheist discrimination as well as between higher concealment and higher psychological distress. Unexpectedly, higher concealment of atheist identity was associated with higher anti-atheist discrimination and, contrary to previous studies, higher disclosure was associated with higher psychological distress. Notably, there was no significant relationship between anti-atheist discrimination and psychological distress in the final model. Implications for future research, training, and practice are provided

FRASQUES : A Question-Answering System in the EQueR Evaluation Campaign

à paraîtreInternational audienceQuestion-answering (QA) systems aim at providing either a small passage or just the answer to a question in natural language. We have developed several QA systems that work on both English and French. This way, we are able to provide answers to questions given in both languages by searching documents in both languages also. In this article, we present our French monolingual system FRASQUES which participated in the EQueR evaluation campaign of QA systems for French in 2004. First, the QA architecture common to our systems is shown. Then, for every step of the QA process, we consider which steps are language-independent, and for those that are language-dependent, the tools or processes that need to be adapted to switch for one language to another. Finally, our results at EQueR are given and commented; an error analysis is conducted, and the kind of knowledge needed to answer a question is studied

Towards a decision support framework for system architecture design

Early phase design phases of more and more complex systems enhance the need for a more interdependent decision-making process across design disciplines and processes. No clear system architecture design process in industry identifies support tools for system architects' need. In this paper, we conducted interviews and workshop with system architects in a major aerospace company in order to understand what system architecture design process is and what decision support tools are needed in this process. The analysis of the collected data has underlined 10 different decision domains that we define and link to the needs expressed by the systems architects interviewed

Comparability measurement for terminology extraction

Proceedings of the Workshop CHAT 2011: Creation, Harmonization and Application of Terminology Resources. Editors: Tatiana Gornostay and Andrejs Vasiļjevs. NEALT Proceedings Series, Vol. 12 (2011), 3-10. © 2011 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/16956