Jessica Pidoux
Biographic Data
| ID | 4168329 |
|---|---|
| NAME | Jessica Pidoux |
| GIVEN NAMES | Jessica |
| FAMILY NAME | Pidoux |
| SIGNATURE | PIDOUX J |
| AFFILIATIONS | Institut d'Etudes Politiques de Paris |
| ORCID | 0000-0001-5705-6230 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Gaining transparency in Uber’s algorithmic management
This empirical study sheds light on Uber’s algorithmic management and provides the first calculation of working time with Uber drivers in Paris to understand the way digital platforms transform the temporalities of work. Based on the personal data of 12 Parisian Uber drivers, we show how Uber organizes drivers’ work through the allocation of trips and calculation of distances according to three distinct working-time units: “searching for, approac…
Governing work through personal data
This article presents an ethnographic account of the advocacy initiative, conducted by NGO PersonalData.IO and the company Hestia.ai, that seeks to empower gig workers by helping them regain access to their personal data through data access rights, using the European Union General Data Protection Regulation. It is based on a case study of Uber drivers in Geneva that has a worldwide relevance for the gig economy. Previously self-employed, drivers …
A comparative study of algorithmic–user classification practices in online dating
Dating-app graphical user interface (GUI) structures for data collection contain categories that enable classifying users algorithmically and classifying users between each other to define their sexuality and find a date. Indeed, app providers define categories that mediate the users’ bodies and interactions to present themselves, and these categories ultimately serve app algorithms for recommending profiles. Categories establish a main reciproca…
No prominent works on this page.
A comparative study of algorithmic–user classification practices in online dating
Dating-app graphical user interface (GUI) structures for data collection contain categories that enable classifying users algorithmically and classifying users between each other to define their sexuality and find a date. Indeed, app providers define categories that mediate the users’ bodies and interactions to present themselves, and these categories ultimately serve app algorithms for recommending profiles. Categories establish a main reciproca…
Governing work through personal data
This article presents an ethnographic account of the advocacy initiative, conducted by NGO PersonalData.IO and the company Hestia.ai, that seeks to empower gig workers by helping them regain access to their personal data through data access rights, using the European Union General Data Protection Regulation. It is based on a case study of Uber drivers in Geneva that has a worldwide relevance for the gig economy. Previously self-employed, drivers …
Gaining transparency in Uber’s algorithmic management
This empirical study sheds light on Uber’s algorithmic management and provides the first calculation of working time with Uber drivers in Paris to understand the way digital platforms transform the temporalities of work. Based on the personal data of 12 Parisian Uber drivers, we show how Uber organizes drivers’ work through the allocation of trips and calculation of distances according to three distinct working-time units: “searching for, approac…
Computer Science (3 works) · Data science (2 works) · Digital Economy and Work Transformation (2 works) · Artificial Intelligence (1 work) · Big data (1 work) · Blockchain Technology Applications and Security (1 work) · Business (1 work) · Categorical variable (1 work) · Computer security (1 work) · Data mining (1 work)