A Lost Opportunity? Collective Demands and Migrant Farmworkers in Costa Rica during the Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic induced an overexposure of migrant farmworkers’ poor working and living conditions in Costa Rica’s northern border area and underscored the country’s dependence on migrant labor. This created a unique opportunity to position pro-migrant concerns and demand actions from the state. In this article, we assess if and to what extent the actions of the Costa Rican state were influenced by migrant demands, or whether other priorities guided policy. Based on a novel database on protest and collective action (Protestas-IIS) that is fed with national and local newspaper articles, we analyze the demands made by migrants, the private sector and NIMBY movements, and state responses. Our findings suggest that the latter prioritized market concerns and antiimmigrant interests, thereby underscoring lessons from the literature that migrants are among the politically most disenfranchised in society. Their demands were only partially responded to by the state, and only concerning issues that aligned directly with public concerns, in this case related to health.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".