奎克的藏经阁 · 原书印刷页

Migrant Labour in the Gig Economy The Intersection of Migrant Labour, Platform Capitalism, and Resistance · 第 68 页

PDF 物理页索引 82 · Dynamics ofVirtual Work

书名
Migrant Labour in the Gig Economy The Intersection of Migrant Labour, Platform Capitalism, and Resistance
作者
未记录
印刷页
68
PDF 物理页
82(从 0 开始)
章节
Dynamics ofVirtual Work
UUID
ce325a04-5bc9-4819-a776-439d90410b32
来源类型
original_book
页面 SHA-256
d67e3617c2cf7a58c3a9357fcf5650b149420387716f929fab1384488e3ee95f

In the following paragraphs, we will examine some expressions of digital caporalato present in the gig economy that outline a situation of exploitation. The empirical material has been gathered within the framework of a broader multi-sited research on last-mile logistics platforms between Italy and Argentina carried out between 2019 and 2022. Data has been collected through an ethnography of work in the two contexts of study; more than 60 interviews were conducted with platform workers, in addition to long periods of participant observation (in the case of Italy, I was employed as a rider for one of the biggest food delivery companies present in the country, while in Argentina I approached the ride-hailing sector mainly as a passenger) and online ethnography through social media and collective chats among workers. An important part of the data also comes from secondary sources, such as court documents and newspaper articles. In the context of food delivery, Italy has unveiled through judicial investigations an illicit network of intermediation operated by a small company subcontracting services to Uber. In the case of ride-hailing, as revealed in the Buenos Aires scenario, a mechanism of digital caporalato finds space within the Uber Driver app itself and can be implemented by the drivers themselves, exposing their colleagues to scams and the risk of compromising their own accounts. In addition to these practices that immediately evoke the concept of a gangmaster, there are more discreet forms of illicit labour intermediation and exploitation of vulnerability, such as the use of bots by riders to enhance their work performance.

68

G. PETERLONGO