Turking in a Global Labour Market

David Martin, Jacki O’Neill, Neha Gupta, Benjamin V. Hanrahan

Research output: Contribution to journalArticlepeer-review

60 Scopus citations


This paper examines how working in the global labour market of Amazon Mechanical Turk (AMT) impacts upon and is understood by two different groups of workers. To do this we report on two qualitative studies; one of US and another of Indian crowdworkers (or ‘Turkers’) that we analysed from an ethnomethodological orientation. Our data is naturalistic and comes from a variety of sources—interviews, observations and forum posts—where Turkers describe their work, and their understandings of that work and of the transnational market they work in. We compare and contrast their situations, their reflections on the marketplace and its global reach, and we take a look at their understandings of one another. Our focus is on ‘the work to making turking work’ (Martin et al. 2014). That is, the work that turkers do to organise and make sense of their work as they operate in the AMT marketplace, such that they can do so effectively. AMT is a technologically mediated marketplace—that is the distribution, completion and payment of work is done online, almost completely through the AMT platform. The design of the platform has important consequences for how Turkers experience and understand the market (including its global or transnational nature). We discuss how our findings relate to a variety of CSCW issues and provide an initial examination of how they relate to globalisation both as a mundanely experienced phenomenon and as a topic of academic interest. We finish the article by drawing on our own experiences in research and design to look at how technology can be used to intervene in a market like this to try to address imbalances in power and agency between employers and workers.

Original languageEnglish (US)
Pages (from-to)39-77
Number of pages39
JournalComputer Supported Cooperative Work: CSCW: An International Journal
Issue number1
StatePublished - Feb 1 2016

All Science Journal Classification (ASJC) codes

  • General Computer Science


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