The Experimental Hand: How Platform-based Experimentation Reconfigures Worker Autonomy
Bibliographic record
Abstract
We examine how platform-based experimentation influences worker autonomy when workers do not have access to the same relational opportunities that workers in conventional bureaucratic organizations have traditionally relied on to preserve their autonomy. By analyzing longitudinal qualitative data from one of the world’s largest digital labor platforms, we found that the platform implemented three experimentation regimes—explicit, concealed, and unbounded—that reconfigured workers’ autonomy in unexpected ways. We theorize the introduction of and successive changes in platform-based experimentation as constitutive of the experimental hand. Our model of the experimental hand captures how successive changes in platform-based experimentation regimes reconfigure workers’ degree of autonomy: workers first experienced increased autonomy, followed by diminished autonomy, and finally workers normalized their diminished autonomy as a “business as usual” aspect of work life on the platform. Whereas prior research has primarily examined the design and efficacy of experiments from the perspective of organizations, our study builds new theory on the social effects of experimentation, capturing the implications faced by workers.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".