Bibliographic record
Abstract
Like in other parts of the world, employers in Latin America planned and built company towns and villages to develop extractive industries, make production possible in isolated places, and shape and control the workforce. Company towns contributed to expanding the capitalist and industrial frontier, becoming a common sight from the Andes to the Caribbean coast of Central America. Early studies defined company towns as foreign enclaves and examined the unique characteristics of isolated mining camps and agricultural states. Multinational companies used camps to attract and settle a diverse workforce, and housing, company stores, and social and recreational services were standard, although their quality varied. Companies enforced a strict separation between foreign managers and local workers, a practice that increased tensions and conflicts and undermined the influence of their paternalist agenda. Throughout the twentieth century, large-scale mining and petroleum exploitations radically transformed the local ecology, and the camps and the plants became symbols of modernity but also environmental destruction. Violence also defined the history of export and resource company towns, and many of these places became sites of state and company repression, such as the case of the banana strikes. Recent studies have moved away from a strict definition of enclave, arguing that workers developed many social, cultural, and political connections with the outside world. Except for textile mills and their vilas opérarias in Brazil, classic factory towns, such as the ones that characterized the industrial landscape of the United States, Canada, and western Europe, were less common in Latin America. Instead, large factories built or subsidized neighborhoods and offered some social and recreational services. In some cases, such as the cement, steel, or meatpacking industry, companies were the most important employers. While they did not officially own the town, they exerted a strong influence outside the factory walls. A rich labor historiography has explored the experience of industrial workers, including the impact of company housing and other paternalistic practices. Local history, oral interviews, and a bottom-up approach have contributed to documenting the complexity of workers’ identity, the role of women and families, and the many forms of resistance and adaption. Company towns were also built around railroads, ports, military bases, and construction sites. While these villages varied in size, they usually shared a common discourse and were made not just to house people but to create a modern and loyal workforce. By the end of the twentieth century, neoliberal reforms, industrial restructuring, and privatization of large state companies made company towns obsolete. Processes of closure have been marked by unemployment, displacement, and dispossession, which have had long-term consequences for workers, families, and local communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".