The Human Side of Regions: Informal Cross-border Traders in the Zambia–Malawi–Mozambique Growth Triangle and Prospects for Integrating Southern Africa
Bibliographic record
Abstract
This paper examines the activities of informal cross-border traders (ICBTs) in the contiguous borderlands of Zambia, Malawi and Mozambique, in order to determine the replicability and feasibility of the growth triangle phenomenon, which was imported as a concept for economic development from Southeast Asia. It also seeks to establish whether ICBTs can satisfy their economic needs from cross-border trade. Apart from the thorough review of relevant literature, participant observations, face-to-face interviews and focus group discussions were deployed to collect the data for the analysis contained in the paper. Primary data from the fieldwork conducted at various locations in the borderlands is qualitatively and statistically analyzed. ICBTs in these areas include affiliates of traders’ associations and non-affiliates. The contiguous borderlands of the three countries comprise a young population of ICBTs with low incomes who have spent relatively few years in cross-border trade. ICBTs who have been longer in the informal trade business have graduated into formal traders. ICBT activities highlight their contribution to regional integration, from the bottom up. Informal cross-border trade provides employment and livelihoods, placing ICBTs outside extremely poor populations living below USD$1.25 per day. ICBTs also have innovative informal ways of accessing credit based on personal interactions and shared experiences with suppliers of goods. Legally establishing the growth triangle creates an environment that ICBTs exploit in order to satisfy their economic needs, especially with government facilitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".