Chapter 3 Platforms at Work: Automated Hiring Platforms and Other New Intermediaries in the Organization of Work
Abstract
This chapter lays out a research agenda in the sociology of work for a type of data and organizational intermediary: work platforms. As an example, the authors employ a case study of the adoption of automated hiring platforms (AHPs) in which the authors distinguish between promises and existing practices. The authors draw on two main methods to do so: critical discourse analysis and affordance critique. The authors collected and examined a mix of trade, popular press, and corporate archives; 135 texts in total. The analysis reveals that work platforms offer five core affordances to management: (1) structured data fields optimized for capture and portability within organizations; (2) increased legibility of activity qua data captured inside and outside the workplace; (3) information asymmetry between labor and management; (4) an “ecosystem” design that supports the development of limited-use applications for specific domains; and (5) the standardization of managerial techniques between workplaces. These combine to create a managerial frame for workers as fungible human capital, available on demand and easily ported between job tasks and organizations. While outlining the origin of platform studies within media and communication studies, the authors demonstrate the specific tools the sociology of work brings to the study of platforms within the workplace. The authors conclude by suggesting avenues for future sociological research not only on hiring platforms, but also on other work platforms such as those supporting automated scheduling and customer relationship management.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
As AHSs become ever more popular, especially in precarious sectors such as retail and the gig economy where prospective employees may have little economic power or knowledge of rights, this is a serious problem.
“As AHSs become ever more popular, especially in sectors which are precarious, such as retail and the gig economy where prospective employees (or contractors) may have little economic power or knowledge of rights [7,15], this is, we argue, a serious problem.”
From What does it mean to 'solve' the problem of discrimination in hiring?: social, technical and legal perspectives from the UK on automated hiring systems (2020) · cites this paper as [7]
These companies are part of standardising not only managerial techniques but also how we should both understand and 'solve' the problem of discrimination in hiring, within a potentially global market.
“This is particularly important as these companies are part of standardising not only managerial techniques [7], but also how we should both understand and 'solve' the problem of discrimination in hiring, within a potentially global market.”
From What does it mean to 'solve' the problem of discrimination in hiring?: social, technical and legal perspectives from the UK on automated hiring systems (2020) · cites this paper as [7]
Literature on bias mitigation in AHSs is at an early stage and so far primarily focused on the US context of employment both socially and legally.
“While algorithmic bias generally and in employment law specifically [14] has had extensive investigation in the FAT* community, literature on bias mitigation in AHSs is at an early stage and so far primarily focused on the US context of employment both socially and legally [7,15,40].”
From What does it mean to 'solve' the problem of discrimination in hiring?: social, technical and legal perspectives from the UK on automated hiring systems (2020) · cites this paper as [7]
The citation lists haven’t been fetched yet
References 62 · Cited by 58
- Authors
- Ajunwa, I., & Greene, D.
- Affiliations
- Harvard University (US)
- University of Maryland, College Park (US)
- ORCID
- Greene, Daniel
- Venue
- Research in the Sociology of Work
- Publisher
- Emerald Publishing Limited
- Published
- 2019-06-14
- Pages
- 61-91
- ISSN
- 0277-2833 (ISSN-L)
- OpenAlex
- W2905125924
- Cited by
- 58
- References
- 62
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 7 · 2023: 4 · 2022: 12 · 2021: 12 · 2020: 7 · 2019: 5
- FWCI
- 66.44
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Research in the sociology of work (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
- Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
- Keywords
- work platforms, affordances, information asymmetry, management methods, human capital, data portability, platform capitalism, automated scheduling, customer relationship management, labor relations, legibility
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review