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Why the future of AIED is causal: Arguments for creating a tradition based on causal thinking
No full textSkills, job application strategies, and the gender wage gap: Evidence from online freelancing
Full text linkThis paper examines how worker skills and job application behavior contribute to the gender wage gap on a major online freelancing platform. We observe significant occupational sorting by gender, with women over-represented in lower-paying project categories and tending to earn less than men even within the same categories. The unexplained gender wage gap conditional on education is initially 39.9%, but it narrows to under 2% when accounting for differences in human capital and application strategies. Our analysis shows that application behavior, including job preferences and asking wages, is the primary factor, explaining up to 90% of the wage gap. We also find that women work on longer projects and achieve higher application success rates than men, which helps offset lower hourly earnings by accumulating more work hours. While men have slightly greater platform and traditional work experience it has minimal impact on wage outcomes. These findings suggest that the gender wage gap on the platform primarily reflects distinct usage patterns between men and women
CaLiGraph: A knowledge graph from Wikipedia categories and lists
Full text linkKnowledge graphs (KGs) are increasingly used for solving or supporting tasks such as question answering or recommendation. To achieve a useful performance on such tasks, it is important that the knowledge modeled by KGs is as correct and complete as possible. While this is an elusive goal for many domains, techniques for automated KG construction (AKGC) serve as a means to approach it. Yet, AKGC has many open challenges, like learning expressive ontologies or incorporating long-tail entities. With CaLiGraph, we present a KG automatically constructed from categories and lists in Wikipedia, offering a rich taxonomy with semantic class descriptions and a broad coverage of entities. We describe its extraction framework and provide details about its purpose, resources, usage, and quality. Further, we evaluate the performance of CaLiGraph on downstream tasks and compare it to other popular KGs
The impact of public country-by-country reporting on multinationals' reporting decisions
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