When digital platforms enter informal sectors: work formalization and institutional change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• When entering informal sectors, digital platforms formalize work practices to make them amenable to the platform model. • To enable formalization, platforms engage in institutional changes to alter the sector’s dominant logic. • Platform-enabled formalization involves codifying interactions, standardizing practices, and controlling boundaries. • Platforms shift informal sectors from an informal market logic to a matchmaking logic, then to a service system logic. • The design and governance of digital platforms for informal sectors need to account for the effects of formalization processes. Digital platforms are undermining long-standing formal institutions for the organization of work. However, when they enter informal sectors, they contribute to the opposite effect by increasing the formalization of work activities. In this study, we investigate this hitherto unexamined phenomenon by drawing on a case study of Gojek, one of the largest digital platforms in Southeast Asia. We identify three main mechanisms through which the platform transformed work in an informal transportation sector to make it amenable to integration into their platform model: codifying market interactions, standardizing work practices, and controlling ecosystem boundaries. We develop an understanding of the institutional changes that supported the platform-enabled formalization by noting the shifts in the sector’s dominant institutional logic from an informal market logic to a matchmaking logic, then to a service system logic. We discuss the implications of these institutional changes for the platform and the workers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.016 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it