The chronic shortage of healthcare workers presents significant ethical and legal challenges, particularly regarding the quality of patient care and safety. This paper explores the implications of healthcare worker shortages, focusing on their impact on labor cost, compromised patient care, increased medical errors, and rising malpractice claims. Healthcare institutions face legal risks when they fail to meet mandated staffing ratios, which can result in penalties, fines, and lawsuits. Furthermore, overworked staf…

The 2023 edition of the Workshop on Web Archiving and Digital Libraries (WADL) will explore the integration of web archiving and digital libraries. The workshop aims at addressing aspects covering the entire life cycle of digital resources, including creation/authoring, uploading/publishing, crawling, indexing, exploration, and archiving. It will also explore areas such as archiving processes and tools for 'non-traditional' resources such as social media, scholarly and government datasets, 3D objects, and digital …

In 2003, UNESCO recognized the volatility of our heritage on the web. In response, many Canadian institutions rose to the challenge to preserve our digital heritage. This study examines web archives created by the University of Alberta Libraries relevant to Western Canadian heritage. We examine these collections in order to (1) assess their degree of link rot (which occurs when a website is no longer online) and (2) to determine how extensively these websites have been preserved.

Since the practice of web archiving, or the act of preserving websites as historical, legal, and informational records, become more commonplace in the 2000s, web archives have become valuable sources for historical research. Unfortunately, many archived websites are of low quality and are missing crucial elements. In this paper, we examine the issue of quality and focus on visual correspondence, the similarity in appearance between the original website and its archived counterpart. We examine how the visual corres…

This paper explores the possibility of applying Machine Learning for Machine Translation evaluation.