Citizenshit - the right to flush : sewage management and its meanings in Villa Lamadrid, Buenos Aires, Argentina
Bibliographic record
Abstract
Urban life means your shit is not your problem. It is commonly felt that for urban residents the management of sewage should not be a personal responsibility; instead, disassociation from sewage, its production, presence, disposal, and management is central to participating in a full urban citizenship. Connection to centralized and water-borne sewerage infrastructure affords this luxury of ‘flushing and forgetting,’ not having to know about or have contact with shit after the toilet is flushed (Hawkins, 2006). This thesis is based on three months of fieldwork in Villa Lamadrid, a historically marginalized peri-urban neighborhood in Greater Buenos Aires. The neighborhood lacks connection to a centralized, water-borne sewerage system. During this period I spent considerable time in the neighborhood, engaging in participant observation, and conducted 36 semi-structured interviews with neighborhood residents. I examine how, in the absence of centralized sewerage connection that makes this sanitation imaginary possible, residents work to claim urban citizenship by employing narratives of disassociation from sewage in its visible forms throughout neighborhood. Notable among these is a racialization of shit and the practices that result in its presence in neighborhood streets and zanjas. In addition, as a part of my interviews I presented two sewage management systems appropriate to aspects of the neighborhood’s biophysical conditions, particularly its saturated groundwater table and vulnerability to flooding during storm events. Both of these systems were household level management systems, a common solution provided by development organizations to urban areas not connected to municipal sewerage service. Interviewees in Villa Lamadrid felt these decentralized sewage management options directly undermined the goal of participation in the urban sanitation imaginary, and their claims to full, rights-claiming citizenship by necessitating, and even relying upon, their personal engagement with the management of their own sewage. This research raises important questions regarding expectations of urban sanitation and the paradigms in which we frame sewage management, and, acknowledging the high failure rate of sanitation interventions in poor communities globally, questions of where we are to go from here, in a rapidly urbanizing world where infrastructure already lags behind ever growing demand.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".