Person:
Rozas Domingo, David

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First Name
David
Last Name
Rozas Domingo
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https://hdl.handle.net/20.500.14352/86270
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Universidad Complutense de Madrid
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Informática
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Ingeniería del Software e Inteligencia Artificial
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    Talk Is Silver, Code Is Gold? Beyond Traditional Notions of Contribution in Peer Production: The Case of Drupal
    (Frontiers in Human Dynamics, 2021) Rozas Domingo, David; Gilbert, Nigel; Hodkinson, Paul; Hassan Collado, Samer
    Peer production communities are based on the collaboration of communities of people, mediated by the Internet, typically to create digital commons, as in Wikipedia or free software. The contribution activities around the creation of such commons (e.g., source code, articles, or documentation) have been widely explored. However, other types of contribution whose focus is directed toward the community have remained significantly less visible (e.g., the organization of events or mentoring). This work challenges the notion of contribution in peer production through an in-depth qualitative study of a prominent “code-centric” example: the case of the free software project Drupal. Involving the collaboration of more than a million participants, the Drupal project supports nearly 2% of websites worldwide. This research (1) offers empirical evidence of the perception of “community-oriented” activities as contributions, and (2) analyzes their lack of visibility in the digital platforms of collaboration. Therefore, through the exploration of a complex and “code-centric” case, this study aims to broaden our understanding of the notion of contribution in peer production communities, incorporating new kinds of contributions customarily left invisible.
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    The platform belongs to those who work on it! Co-designing worker-centric task distribution models
    (2021) Rozas Domingo, David; Saldivar, Jorge; Zelickson, Eve
    Today, digital platforms are increasingly mediating our day-to-day work and crowdsourced forms of labour are progressively gaining importance (e.g. Amazon Mechanical Turk, Universal Human Relevance System, TaskRabbit). In many popular cases of crowdsourcing, a volatile, diverse, and globally distributed crowd of workers compete among themselves to find their next paid task. The logic behind the allocation of these tasks typically operates on a "First-Come, First-Served" basis. This logic generates a competitive dynamic in which workers are constantly forced to check for new tasks. This article draws on findings from ongoing collaborative research in which we co-design, with crowdsourcing workers, three alternative models of task allocation beyond "First-Come, First-Served", namely (1) round-robin, (2) reputation-based, and (3) content-based. We argue that these models could create fairer and more collaborative forms of crowd labour. We draw on Amara On Demand, a remuneration-based crowdsourcing platform for video subtitling and translation, as the case study for this research. Using a multi-modal qualitative approach that combines data from 10 months of participant observation, 25 semi-structured interviews, two focus groups, and documentary analysis, we observed and co-designed alternative forms of task allocation in Amara on Demand. The identified models help envision alternatives towards more worker-centric crowdsourcing platforms, understanding that platforms depend on their workers, and thus ultimately they should hold power within them.