Necrospatial containment and slow violence in Harare’s informal settlements
Bibliographic record
Abstract
This paper develops the concept of necrospatial containment (NSC) to illuminate the conditions shaping everyday life in Hopley and Hatcliffe Extension, Harare’s largest informal settlements. Building on Mbembe’s (2003) necropolitics and Nixon’s (2011) theory of slow violence, I develop necrospatial containment as an analytical framework structured around four interrelated pillars: (i) geographies of spatial constriction, (ii) infrastructure as deathscape, (iii) perpetual threat of erasure, and (iv) toxic ecologies. Collectively, these pillars reveal how urban governance, infrastructural abandonment, and everyday struggles intersect to produce spaces of prolonged disposability. I then empirically ground necrospatial containment using evidence from focus group discussions and institutional discourses, demonstrating how informal settlement residents are confined in precarious conditions that limit mobility, constrain opportunities, and normalize risk. The paper contributes to critical urban studies by advancing a conceptual vocabulary that frames informality as a spatialized mode of governance that structures who gets to live and under what conditions. The findings underscore the urgent need for policy interventions that recognize informal settlements as legitimate urban spaces requiring investment, rights, and infrastructural justice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 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".