Shifting Formalization Policies and Recentralizing Power: The Case of Zimbabwe's Artisanal Gold Mining Sector
Bibliographic record
Abstract
In the 1990s, government authorities in Zimbabwe introduced internationally praised policies to formalize the artisanal and small-scale mining sector, using a combination of district-administered and nationally administered licensing and capacity-building measures. While “decentralization” efforts in the 1990s and early 2000s were hampered by insufficient resource and power transfers, the model was seen by environmental scholars as a source of optimism. However, as economic crisis deepened in the 2000s, national officials (a) revoked the power of Rural District Councils to regulate riverbed alluvial gold panning and (b) increased barriers to formally licensed small-scale primary ore mining. This article examines the recentralization of power in this growing informal sector, exploring how heavy-handed implementation of national reforms contributed to livelihood insecurity. The study emphasizes how national officials invoked “formalization” rationales for mining policy shifts that obscured their underlying political and economic drivers, disempowering local district authorities and deepening the marginalization of informal livelihoods.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".