| 研究課題/領域番号 |
22K01898
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| 研究機関 | 埼玉大学 |
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研究代表者 |
Noh SungChul 埼玉大学, 人文社会科学研究科, 准教授 (90758492)
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| キーワード | Platform labor / Young workers / Precarious employment / Data Labeling / Machine learning / Generative AI / Remote work |
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| 研究実績の概要 |
The primary goal of the first year of this research project was to collect qualitative data on digital platform labor. I could conduct more than 40 interviews with platform workers in various industries in Korea, including food delivery workers, data labelers, and designated drivers.
These interviews offer insights into the objective(e.g., working conditions) and subjective(e.g., job satisfaction and meanings of work) experiences of platform labor of younger workers. I presented the preliminary findings of my research at international conferences, such as the Academy of Management annual meeting in Seattle. At the conferences, I can validate the importance and timeliness of my research project and get feedback on my research agenda.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
I could make progress more smoothly than initially planned.
First of all, the qualitative data collection went as planned. I could interview 48 young platform workers in Korea who were working in a range of industries.
Second, a network of researchers on platform labor is organized. I manage to bring together junior scholars who have been conducting empirical research on platform labor. We are having an online, bi-weekly meeting in which we read recent scholarly articles together and share the progress in the projects each member is working on.
Finally, I presented the preliminary findings of my research at international conferences. I can get insightful feedback on my research agenda, as well as theorization of collected data.
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| 今後の研究の推進方策 |
I set up two specific goals for this year.
First, data analysis will be initiated. Using Nvivo (the qualitative data analysis tool), I will try to identify theoretical codes emerging from data I collected last year.
Second, I’m planning on additional data collection, which focuses on so-called data-labeling workers. They work remotely via online platforms, and most importantly, their online microtask contributes to the development of generative AI models like ChatGPT. By highlighting their work conditions and labor process, I aim to develop a better understanding of ‘ghost labor’ behind the rapid advancement of AI-related technologies.
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