Women, Migration & the Cashew Economy in Southern Mozambique
Bibliographic record
Abstract
Analyses the lives and livelihoods of the female cashew shellers in Mozambique's capital in the colonial era, during which the industry grew to be a major export, and relates how the women played a fundamental, but previously underappreciated, role in the colony's economy. JOINT RUNNER-UP FOR THE 2017 AIDOO-SNYDER BOOK PRIZE Between the late 1940s and independence in 1975, rural Mozambican women migrated to the capital, Lourenço Marques, to find employment in the cashew shelling industry.This book tells the labour and social history of what became Mozambique's most important late colonial era industry through the oral history and songs of three generations of the workforce. In the 1950s Jiva Jamal Tharani recruited a largely female labour force and inaugurated industrial cashew shelling in the Chamanculo neighbourhood. Seasonal cashew brews had long been an essential component of the region's household, gift and informal economies, but bythe 1970s cashew exports comprised the largest share of the colony's foreign exchange earnings. This book demonstrates that Mozambique's cashew economy depended fundamentally on women's work and should be understood as "whole cloth". Drawing on over 100 interviews, the rich narratives convey layered histories: the rural crises that triggered the flight of women, their lives as factory workers, widespread payment and wage fraud, the formation of innovative urban families, and the health costs that all African families paid for municipal neglect of their neighbourhoods. Jeanne Marie Penvenne is Professor of History, and core faculty in International Relations, Africana and Women, and Gender and Sexuality Studies at Tufts University.. She is the author of the Herskovits shortlisted African Workers and Colonial Racism (James Currey/Heinemann, 1995)
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".