Labouring to Choose, Choosing to Labour: Coercion and Choice in the Potosi Mita
Bibliographic record
Abstract
The Spanish colonial labour regime in Latin America was known as the mita, and provided the Indian workers needed for numerous Spanish enterprises. The best known of the mita institutions was the Potosi mita, which lasted from 1573 to 1825. It drafted male Indians from the Viceroyalty of Peru to work in the huge Spanish silver mines at Potosi. The mita placed a heavy burden on the backs of Indian peasants, and adversely affected village life, since many Indians migrated to escape the harsh conditions of the mines. Yet while the Indians suffered as a result of Spanish colonial oppression, it would be a mistake to see them simply as passive victims; in fact, they exercised personal agency in a number of significant ways. One of these hots was by choosing whether to go to the mines or to migrate. Another way was by deciding either to leave Potosi after serving their time of forced labour or to stay on as voluntary workers, which had considerable economic benefits; and indeed, many of them elected to stay. Ironically, in giving the Indians this latter choice, the coercion of the Potosi mita ended up creating the voluntary long-term labour force that the Spanish had hoped for from the start.
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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 | 0.011 | 0.037 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".