Community and company capacity: the challenge of resource-led development in Zambia's 'New Copperbelt'
Bibliographic record
Abstract
Relationships between the extractive industries, society and development are often symbolized by unfulfilled expectations and even conflict. Poor, rural, politically marginalized and indigenous communities are often significantly impacted by the extraction of fuel and non-fuel minerals. This paper explores the challenge of resource-led development in Zambia's ‘New Copperbelt’ (i.e. the Northwestern Province). It explains how Kansanshi, a mid-tier mining company, has struggled with various community development aspects, including resettlement and compensation, hiring and employment, the maintaining of local government interactions and formulating a coherent corporate social responsibility (CSR) and infrastructure project strategy. Findings suggest that community capacity to hold Kansanshi and local government to account is relatively weak. Recommendations include aligning CSR strategies with district, regional and national development objectives, as well as building linkages between local civil society organizations and national/international non-governmental organizations. This would enable communities around the mine to share experiences, lessons learnt and effective company and local government engagement strategies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".