Networked but Commodified: The (Dis)Embeddedness of Digital Labour in the Gig Economy
Bibliographic record
Abstract
This article investigates the (dis)embeddedness of digital labour within the remote gig economy. We use interview and survey data to highlight how platform workers in Southeast Asia and Sub-Saharan Africa are normatively disembedded from social protections through a process of commodification. Normative disembeddedness leaves workers exposed to the vagaries of the external labour market due to an absence of labour regulations and rights. It also endangers social reproduction by limiting access to healthcare and requiring workers to engage in significant unpaid ‘work-for-labour’. However, we show that these workers are also simultaneously embedded within interpersonal networks of trust, which enable the work to be completed despite the low-trust nature of the gig economy. In bringing together the concepts of normative and network embeddedness, we reconnect the two sides of Polanyi’s thinking and demonstrate the value of an integrated understanding of Polanyi’s approach to embeddedness for understanding contemporary economic transformations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.000 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".