Being a turker

By David B. Martin, Benjamin V. Hanrahan, J. O'Neill, Neha Gupta. 2014

340 citations recorded by the source corpus.

Subfields: Communication, Computer Science Applications, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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In Computer Science Applications

In Human-Computer Interaction

Citations in the corpus

CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation (2022, background): “These tools can help workers overcome the information asymmetries built into the AMT platform [33].”
A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turk (2017, background): “This is problematic as income generation is the primary motivation of workers [4,13,44,47].”
We Are Dynamo: Overcoming Stalling and Friction in Collective Action for Crowd Workers (2015, background): “On these platforms they share well-paying work, discuss employers, educate newcomers, and consult with employers who are willing to communicate [30].”
MTurk Character Misrepresentation: Assessment and Solutions (2017, background): “A number of researchers have documented the frustration and difficulty associated with being a Turker (Dholakia 2015; Martin et al. 2014).”
Striving to Earn More: A Survey of Work Strategies and Tool Use Among Crowd Workers (2018, background): “Low per-task re-wards and unpaid task search time contribute to more than half of the AMT workers currently earning less than $5 an hour (Ipeirotis 2010; Irani and Silberman 2013; 2016; Hitlin 2016; Horton and Chilton 2010; Martin et al. 2014; Hara et al. 2018).”
Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers (2015, methodology): “Following the approach used in [27], we sampled 128 online forum posts and comments mentioning the algorithmic features selected out of thousands made in a five-month period.”
Fair Work: Crowd Work Minimum Wage with One Line of Code (2019, background): “Microtask crowdsourcing remains a precarious income source for crowd workers (Gray and Suri 2019; Kittur et al. 2013; McInnis et al. 2016; Martin et al. 2014; Hara et al. 2018).”
Examining Crowd Work and Gig Work Through the Historical Lens of Piecework (2017, background): “Workers are often blamed for any low–quality work, regardless of whether they are responsible [104, 106].”
Algorithms at Work: The New Contested Terrain of Control (2020, background): “…Amazon Mechanical Turk platform, “ requesters ” (e.g., employers) could rate workers but workers could not rate requesters; this information asymmetry made it difficult for workers to sanction abusive clients and prevented other workers from learning which clients to avoid (Martin et al., 2014).”
Conducting Clinical Research Using Crowdsourced Convenience Samples. (2016, background): “, time to payment and reasons for denying payment) are clearly articulated before workers accept the HIT (Martin et al. 2014).”
Daemo: A Self-Governed Crowdsourcing Marketplace (2015, background): “A common complaint [3]: “We can be rejected yet the requesters still have our articles and sentences.”
Break It Down: A Comparison of Macro- and Microtasks (2015, background): “In crowdsourcing, microtasking has allowed crowd workers greater time flexibility [8].”
Embracing Error to Enable Rapid Crowdsourcing (2016, background): “Because platforms strongly punish errors, workers carefully examine even straightforward tasks to make sure they do not represent edge cases [40, 22].”
The Expertise Involved in Deciding which HITs are Worth Doing on Amazon Mechanical Turk (2021, background): “Crowdworkers on Amazon Mechanical Turk (AMT) – also known as Turkers – depend on the platform as an important source of income [11, 32, 50], with some Turkers referring to the platform as a ‘safety net’ [38].”
Quantifying the Invisible Labor in Crowd Work (2021, background): “From the workers’ perspective, these markets provide a central place to find work and offer them the flexibility of working from wherever they desire [1, 87].”
A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality (2016, background): “As they progress through these tasks, questions arise and they often seek help by communicating with other workers or the task creator [39].”
“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI (2021, background): “[79], and among frontline health workers in India by Ismail and Kumar [58].”
Digital labour platforms and the future of work (2018, background): “54 diGiTAL LAbour PLATForMS ANd THe FuTure oF worK This indicates the presence of a “dual-banded pay-rate marketplace” (Martin et al., 2014, p. 8).”
A Glimpse Far into the Future: Understanding Long-term Crowd Worker Accuracy (2016, background): “Furthermore, on external forums and in collectives, workers often share well-paying work opportunities, teach and learn from other workers, review requesters, and even consult with task creators to give constructive feedback [19, 38, 40, 48].”
The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation? (2016, neutral): “Workers discuss these issues in online forums such as ‘Turker Nation’ (Martin et al., 2014) and also on the activist platform ‘Turkopticon’, where they help each other by making public and evaluating their experiences with the employers (Irani & Silberman, 2013).”