Experiments and Counter‐Experiments in the Urban Laboratory of Water‐ Supply Partnerships in India
Bibliographic record
Abstract
Abstract Karen Bakker has characterized the scattered islands of networked water supply that are common in the cities of the global South as ‘archipelagos’. Those living outside of archipelagos utilize a variety of interventions, collectively referred to here as tendrils, to access water by informal means. Neoliberal imperatives driving infrastructure transformation aim to alter the paradigm of water‐supply provision to diminish its plural composition and effectively transform tendrils into archipelagos. In this article, developing a conceptual and methodological synthesis between Science and Technology Studies (STS) and political ecology, I study the emergence of public‐private partnerships in India as laboratories in the marketization of water‐supply provision. These partnerships, initiated at local scales, aim to enroll informal water users into standardized modes of water‐supply provision and effectively expand the archipelagos of modernity. I draw upon empirical research of a water‐supply partnership in the city of Bengaluru, describing some of the characteristics of the experimental processes, and argue that they simultaneously forward the marketization of water‐supply services while inadvertently providing opportunities for residents, local associations and activists to form networks of counter‐experimentation. The description of these political acts, this article concludes, provokes re‐examination of the efficacy of an instrumental understanding of water partnerships, but requires closer policy engagement with ‘governance failures’ that are rife in water‐supply provision.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".