Technics of Labor: Productivism, Expertise, and Solid Waste Management in a Public‐Private Partnership
Bibliographic record
Abstract
Abstract In Lahore, a public‐private partnership has been formed to replace the Solid Waste Management (SWM) Department. Along with technological and managerial interventions into the labor process, this partnership has also brought in a class of professionals whose expertise is viewed as being essential to improving solid waste management for the city. Nevertheless, a labor force of sanitation workers and supervisors from the municipal SWM Department remain the primary means by which discarded materials are actually taken away across the urban landscape. This article examines how technical and productivist frameworks were brought to bear—especially as professionals enacted their expertise—upon the labor process by which waste materials are disposed of in the city. In doing so, this article argues that in moments of institutional and technological transition, the instability of work as a category of action opens it up to potential revaluation. Not only does this approach make clear the frameworks, whether technical or productivist, through which forms of work or labor get revalued, it also allows us to trace a politics of work beyond such frameworks.
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".