Empowering Refugee Claimants and their Lawyers: Using Machine Learning to Examine Decision-Making in Refugee Law
Our project aims at helping and supporting stakeholders in refugee status adjudications, such as lawyers, judges, governing bodies, and claimants, in order to make better decisions through data-driven intelligence and increase the understanding and transparency of the refugee application process for all involved parties. This PhD project has two primary objectives: (1) to retrieve past cases, and (2) to analyze legal decision-making processes on a dataset of Canadian cases. In this paper, we present the current state of our work, which includes a completed experiment on part (1) and ongoing efforts related to part (2). We believe that NLP-based solutions are well-suited to address these challenges, and we investigate the feasibility of automating all steps involved. In addition, we introduce a novel benchmark for future NLP research in refugee law. Our methodology aims to be inclusive to all end-users and stakeholders, with expected benefits including reduced time-to-decision, fairer and more transparent outcomes, and improved decision quality.
Code (0)
등록된 구현이 없습니다.
Tasks
Decision MakingSimilar Papers 제목 키워드 기반
Automated Refugee Case Analysis: An NLP Pipeline for Supporting Legal Practitioners
In this paper, we introduce an end-to-end pipeline for retrieving, processing, and extracting targeted information from legal cases. We investigate an under-studied legal domain with a case study on refugee law in Canada…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NERUsing massive health insurance claims data to predict very high-cost claimants: a machine learning approach
Due to escalating healthcare costs, accurately predicting which patients will incur high costs is an important task for payers and providers of healthcare. High-cost claimants (HiCCs) are patients who have annual costs a…
BIG-bench Machine LearningBinary ClassificationManagementFrom Zero to Production: Baltic-Ukrainian Machine Translation Systems to Aid Refugees
In this paper, we examine the development and usage of six low-resource machine translation systems translating between the Ukrainian language and each of the official languages of the Baltic states. We developed these s…
Machine TranslationTranslationThe changing dynamics of HIV/AIDS during the Covid-19 pandemic in the Rohingya refugee camps in Bangladesh a call for action
COVID-19 pandemic has affected each and every country's health service and plunged refugees into the most desperate conditions. The plight of Rohingya refugees is among the harshest. It has severely affected their existi…
ManagementRites de Passage: Elucidating Displacement to Emplacement of Refugees on Twitter
Social media deliberations allow to explore refugee-related is-sues. AI-based studies have investigated refugee issues mostly around a specific event and considered unimodal approaches. Contrarily, we have employed a mul…