Labor space
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Park, Jaehyuk | - |
dc.contributor.author | KIM, Seongwoon | - |
dc.date.accessioned | 2023-12-30T16:30:12Z | - |
dc.date.available | 2023-12-30T16:30:12Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://archives.kdischool.ac.kr/handle/11125/51538 | - |
dc.description | Thesis(Master) -- KDI School: Master of Public Policy, 2023 | - |
dc.description.abstract | The labor market is a complex ecosystem comprising multiple economic units such as skills, jobs, industries, and firms. Hence, a true understanding of the labor market requires a holistic perspective that considers the interrelationships between these entities. However, existing studies have often focused on single or bipartite units; therefore, they don’t capture the reciprocal effect of heterogeneous units of the labor market. Here, we introduce Labor Space, a high-dimensional space created by a large language model. Labor Space maps industry, firm, occupation, and skill to a unified embedding space representing the conceptual similarity of the labor market entities. Alignment of conceptual dimensions, such as the production-healthcare axis, reveals our numerical representation portrays the industrial structure of the labor market. Moreover, the calculation of the embedding vector catches the latent relationship of the labor market entities and their interactions with external factors, such as the impact of AI on the labor market. Labor Space offers a comprehensive and innovative approach to understanding the interconnectedness of entities within the labor market, providing a pragmatic tool for researchers, policymakers, and business leaders | - |
dc.description.tableOfContents | 1. Introduction 2. Related Works 3. Data and Methods 4. Landscape of Labor Space 5. Mapping heterogeneous units on conceptual axis 6. Vector calculation for economic analogy 7. Estimating the impact of AI 8. Discussion 9. Appendix 10. Reference | - |
dc.format.extent | 33 p | - |
dc.publisher | KDI School | - |
dc.subject | Labor market--Econometric models | - |
dc.title | Labor space | - |
dc.title.alternative | a high-dimensional representation of the labor market via large language models | - |
dc.type | Thesis | - |
dc.contributor.department | KDI School, Master of Public Policy | - |
dc.description.isOutstanding | Outstanding | - |
dc.date.awarded | 2023 | - |
dc.description.degree | master | - |
dc.description.eprintVersion | published | - |
dc.type.DSpace | Outstanding master | - |
dc.publisher.location | Sejong | - |
dc.description.statementOfResponsibility | Seongwoon KIM | - |
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