Waste Collection Technologies, Informal Waste Pickers, and Urban Exclusion: A Case Study of Calgary
Bibliographic record
Abstract
Waste management engineers and administrators have conceived of technological efficiency and optimization as the “modern” way to sustainable waste collection and management. This instrumental ideology of technology offers a progressive chant for modern waste collection technologies and a less enthusiastic one for the tools and techniques of informal waste pickers. Few efforts have gone into conceptualizing the social context and implication of waste collection technologies. In this thesis, I used a qualitative case study to explore the impact of residential waste collection technologies on the exclusion of informal waste pickers in Calgary. I draw on Andrew Feenberg's critical theory of technology to situate waste collection technologies within social, economic, and political contexts in Calgary. I argue that the social relations of ownership and control over waste collection technologies in Calgary illustrate complex and contested values, norms, and privileges, which create an unequal social, material, and technical relationship contributing to the exclusion of pickers and the exploitation of labor and waste. Calgary’s new curbside program protects the social norms of private asset ownership and consumerism, as well as the interest of private homeowners and some bureaucratic and large capitalist individuals in Calgary. A local third-sector organization, Calgary Can, has resisted these acts through its hook program; local bottle pickers have also resisted them through their collection activity and technologies. These realities push back against the colloquial understanding of modern waste collection technologies as value-free, a conception that dominates academic research and city policies and programs in waste management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.012 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| 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".