Sustainable Urban Livelihoods and Marketplace Social Capital: Crisis and Strategy in Petty Trade
Bibliographic record
Abstract
Urban growth has been accompanied by the development of bimodal labour markets and increasing inequalities in both North and South. In Southern cities, many of the poor have turned to the informal sector, in particular to street trade. This has resulted in a multiplicity of urban conflicts and has led to pressure on urban managers to undertake formalisation, for which an increasingly developmental approach has been advocated. Nevertheless, for traders, the formalisation of street trade has very uneven outcomes. The starting-point for this article is the premise that not enough is known about the social fabric upon which trading careers depend. Adopting sustainable livelihoods as a conceptual framework and drawing on social capital theory, four questions are addressed. How do trading careers survive over time? Are there differences in the survival strategies for which social capital is employed among traders operating in different political, cultural and socioeconomic contexts? In the new processes of urbanisation, are the old relationships on which social capital is based, simply lost in the new, or are traditional networks and structures adapted? Finally, what policy conclusions should be drawn to inform urban management practices as they relate to trade formalisation? The primary findings are that marketplace social capital is increasingly important to traders' economic capital. However, inherited ties, although they diminish in importance, continue to be valuable and often serve as the basis for the development of contingent ties. Implications are discussed for urban management and planning practice, for planning theory and for social capital theory.
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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 | 0.005 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| 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".