MétaCan
Menu
Back to cohort

Necrospatial containment and slow violence in Harare’s informal settlements

2025· article· en· W7116843483 on OpenAlexaff
Elmond Bandauko

Bibliographic record

VenueGeoforum · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInformal settlementsCorporate governanceNegotiationHuman settlementSettlement (finance)UrbanizationPsychological interventionContainment (computer programming)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.269
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueGeoforumSame topicUrban Planning and GovernanceFrench-language works237,207