Migration, authority and the gendered organization of labour in artisanal gold mining in Sierra Leone (and Mozambique)
Bibliographic record
Abstract
Abstract Recent studies of migration into artisanal and small-scale mining (ASM) have explored the motivations, strategic agency and professional trajectories of women and men miners who move to mine. In this article, I seek to shift the focus from the ‘push/pull’ factors in migration to consider the varied entanglements of mobility with authority and power relations pervasive through rural institutions. The importance – or lack of importance – of being a ‘migrant’ in these mining sites rests largely on the particular gendered cultural politics shaping livelihoods in the area. Drawing principally on ethnographic research in Tonkolili District, Sierra Leone, this article examines how migrant status for men and women working in the gold sites who came from other parts of the country is more marked than for Zimbabwean migrants working in artisanal gold mines in Manica, Mozambique. I argue that migrant status is marked by various authority and power relations in artisanal gold-mining sites when those controlling access to mining livelihoods, including access to residency in the mining communities, are able to emphasize contingent forms of belonging by migrants compared with those defined as ‘locals’. Critical to these differential forms of valuation is the particular organization of labour.
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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 | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".