Complementing or Conflicting Rationalities? How Self-Production Practices in Collective Spaces Can Shape Urban Planning: Insights from Maputo City
Bibliographic record
Abstract
Abstract Spatial planning and governance in African cities are often framed and conceived through the formal-informal binary. This view has been responsible for negative connotations that increase urban populations’ vulnerability. Moreover, it has been heavily criticised as presenting a reductive view of urban development. Alternative framings such as “alternative informality” and “self-production” have recently contested such views by proposing process-oriented approaches that recognise the legitimacy of informal praxis. However, research on self-production practices has tended to focus on the household or municipal level, neglecting what can be termed “collective space”. This chapter explores the production and use practices within collective spaces based on research conducted in two peripheral neighbourhoods in Maputo in 2019. The findings highlight the role and legitimacy of self-production practices in collective space to provide services, consolidate local governance and substantiate urban development. It finds that the role of local residents and authorities in urban planning has only tentatively been accepted by official municipal-level planning agencies. The chapter will reflect on how collective space can better overcome local challenges beyond the household level and represent potentialities for inclusive and democratic planning. However, there are still many challenges in collective space that remain poorly addressed.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".