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Merit and monetisation: A study of video game user-generated content policies
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“There are types of work which have been relocated into domestic spaces and are entirely online, such as the monetization of leisure interests as content creation (Thomas 2023), online crowdwork (Bergvall-Kåreborn and Howcroft 2014; Hertwig et al. 2024) and digital nomadism (Aroles et al. 2020).”
From Reflections on Sociotechnical Change: New Directions for and Continuities in Research on New Technology, Work, and Employment (2026) · cites this paper as Thomas 2023
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Research works printed but not linked: 29
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Cited by
Howcroft, D., Lucio, M. M., & Taylor, P. (2026) · New Technology, Work and Employment · doi:10.1111/ntwe.70049 · Cited by 1
Metadata
- Authors
- Thomas, A.
- Venue
- Internet Policy Review
- Published
- 2023-03-03
- Volume
- 12
- Issue
- 1
- ISSN
- 2197-6775
- Cited by
- 1
- References
- 0
- Language
- en
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.