Ride Hailing Regulations in Cali, Colombia: Towards Autonomous and Decent Work
Bibliographic record
Abstract
In this article we explore the decent work standard developed by Richard Heeks for digital online labour markets and use a review of empirical research about ride-hailing to adapt this framework to the location-based service delivery market. The framework is then tested against an in-depth analysis of informality and precarity in the ride hailing sector in Cali, Colombia. Findings show that location-based platform workers in Cali lack many decent work protections. However, the case study also demonstrates that workers are evolving creative ways to grapple with specific aspects of precarity within the ride-hailing sector. Based on this analysis, we argue that policy analysis and worker innovations need to 'meet in the middle' rather than follow policy recommendations emanating from other jurisdictions. We suggest some specific policy reforms that will be appropriate to the Colombian and Latin American context.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".