Bibliographic record
Abstract
Rapid urbanization has worsened the water shortage problem in sub-Saharan African cities, with most people using water from sources other than official water supply systems.However, dominant accounts of why urban households face water shortages remain confined to the formal water sector, with explanations privileging market forces and institutional dynamics as significant barriers, with little or no attention to the role of non-market relations in mediating access to water among households on the periphery of municipal supply grids.Using Mzuzu (Malawi) as a case study, I applied theoretical perspectives grounded in political ecology and feminist political ecology to examine sociocultural and political strategies the poor mobilize to access water for daily use.The findings of qualitative research (n=52) indicate that the urban poor seek to address the problem of water shortage processually, assembling a set of contingent socio-spatial and temporal strategies that allow them to bridge between different spells and sources of water according to household utility purposes.Specifically, the study found that ganyu, an informal form of labour rooted in Malawi's history, granted the urban poor secondary access to the same water supply system from which they are officially excluded.At the same time, material control over water allowed ganyu providers to leverage significant control over the labour of ganyu seekers and women's bodies, suggesting that water is a medium through which historical materializations of colonial labour relations find new expression.The study also reveals that the poor negotiate competing water needs by relying on symbolic meanings and cosmological and cultural beliefs to make sense of water and justify the domestic use of water from otherwise potentially contaminated sources.These findings show the intimate connection and multiscalar integration between the water supply system's formal, impersonal, market realm and the informal, interpersonal non-market social relations of water.Although the design of this study was partially affected by the Covid-19 pandemic, the findings can potentially make significant theoretical and empirical contributions to our understanding of the sociocultural and political forces that shape access to water among the urban poor.The thesis concludes with recommendations and directions for future research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".