Toward supported self-provisioning: Assessing the constraints and generative possibilities of informal modes of urban life
Bibliographic record
Abstract
This paper develops the concept of supported self-provisioning (SSP) to critically examine how residents of structurally disadvantaged urban contexts mobilize informal practices to support livelihoods and secure essential services. Drawing on interdisciplinary literature, the paper situates SSP within broader debates on informality, infrastructure, and subaltern urbanism. SSP is a hybrid form of grassroots city-making that is not entirely autonomous nor wholly dependent on the state. Instead, it emerges through negotiated relations with a range of actors, including local authorities, nongovernmental organizations, political brokers, and community organizations. By synthesizing key debates from urban scholarship, this paper outlines the material, institutional, and spatial dynamics that shape SSP. It identifies the generative possibilities of SSP, such as community cohesion, political visibility, and service innovation. It assesses the structural constraints of (unsupported) self-provisioning, including regulatory exclusion, infrastructural precarity, and uneven forms of state engagement. These generative possibilities and structural constraints help define informality as a mode of urban survival while pointing to avenues of inclusive intervention. SSP contributes to urban theory by offering a nuanced framework to understand how informality operates as a site of governance and grassroots agency. This opens theoretical and applied avenues to intervene in self-provisioning practices through informality by recognizing, legitimizing, and supporting them.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".