Unit:
Specialty Science, Technology, Society-Science and Technology StudiesLibrary of the School of Science
Supervisors info:
Δρακόπουλος Σταύρος, Καθηγητής, Τμήμα ΙΦΕ, ΕΚΠΑ,
Κατσελιδης Ιωάννης, Επίκουρος Καθηγητής, Τμήμα ΙΦΕ, ΕΚΠΑ
Τύμπας Αριστοτέλης, Καθηγητής, Τμήμα ΙΦΕ, ΕΚΠΑ
Original Title:
Technological proficiency in a dataful world; an STS empirical review of Greece-focused labor analytics
Translated title:
Technological proficiency in a dataful world; an STS empirical review of Greece-focused labor analytics
Summary:
This paper explores the perception of skills within the labor economics context under the scope of STS. We examine different takes of theoretical economics on labor skills and their interplay with technology, the conflation between education and skill, and the inability to update its models in line with empirical economics’ findings. We also address critical points towards the widespread human capital-based approaches and their positivistic nature. We explore available labor-related data and how the digital proficiency is measured by European institutions, opening the black box and discussing biases they enclose, focusing on Greece and its respective institutions. We propose the creation of digital intensity indices of occupational group, industry and educational field, and incorporate them with PIAAC data, an international household survey conducted by OECD. We conduct analyses on the attributes’ explanatory power of digital proficiency, using Problem solving in technology rich environments (PSTRE) score as a proxy. We modify the dataset to account for the design complexity of PIAAC, and implement linear regression analyses, as well as an XGBoost regression model. Our findings suggest that the significance of the provided attributes in PIAAC is highly susceptible to the methodology employed. Education is indeed considered significant, but insufficient to explain digital proficiency under a linear relationship. In multiple occasions, activity content at home is considered more significant compared to its professional counterpart, creating an interest for further exploration along with other findings. The paper stands right at the center of STS’s interdisciplinary nature. It examines the sociotechnical implications of the academic discourse regarding the skill content of labor economics. It reveals the available, but concealed, methodologies implemented by European institutions in the creation of indices, which are decontextualized and used as ground truth for relevant policy designs. Technology is prevalent in the content of the empirical analysis, as the variable under examination is the digital proficiency. But it also connects on an instrumental basis, since the models along with data manipulation processes are included in a publicly available python resource, aspiring to be the starting point for further introduction of advanced analytical models to the labor analytics and large scale surveys – currently mostly examined under a linear scope.
Main subject category:
Science
Keywords:
skills, labor economics, sts, theoretical economics, technology, education, educational policy, human capital, digital proficiency, digital skills, technological skills, Greece, institutions, PIAAC, ISIC, ICED, ISCO, ESCO, Cedefop, EU, European Union, VET, education, digital intensity, household survey, problem solving, regression analysis, xgboost, sociotechnical implications, policy designs, technology, data manipulation, python, analytical models, AI, ML, Machine Learning, Artificial Intelligence
Number of references:
110
File:
File access is restricted until 2027-04-24.
STS Thesis - Alevizos Ioannis - Corrected Version.pdf
4 MB
File access is restricted until 2027-04-24.
