Farm-level impacts in Mexico of the participation in Canada's Seasonal Agricultural Workers Program (CSAWP)
Bibliographic record
Abstract
In several parts of the world, the number of poor people in rural areas surpasses the capacity of agriculture to provide employment opportunities. The increasing role of off-farm income has highlighted the importance of rural migration, both within Mexico and to the United States (US) and Canada, as a vehicle for poverty reduction. A significant number of Mexican migrants are participating in guest worker programs, performing mainly agricultural activities. These programs allow Mexicans to enter the US and Canada through formal channels. Canada's Seasonal Agricultural Workers' Program (CSAWP) lets Mexican farmers enter Canada to work legally in agriculture, and participants in this Program send remittances home that are an important contribution to rural development. The main reasons to participate in guest worker programs relate to economic factors, such as the opportunity to earn a relatively high, stable income abroad and the lack of employment opportunities in Mexico, particularly in rural areas. The number of Mexican agricultural workers temporally migrating to Canada through CSAWP has increased significantly over time and now exceeds 12,000 annually. In Mexico, the program provides an estimated C$70 million in remittance income annually, mainly directed to rural and poorer regions. In these regions, this fungible income supports consumption activities and expenditures on family education. However, there are also investments in farming activities, in turn enhancing agrarian incomes. This research explores the impact of remittances on farm investments by migrant workers participating in CSAWP, which in turn impact farm income levels. The results highlight the extent to which temporary migrant labour to Canadian agriculture allows Mexican farmers to enhance their agricultural activities through increased farm investments, such as buying better seeds, fertilizer and farm equipment. The results show that, on the one hand, remittances can significantly enhance farm investments in Mexico that in turn increase farm incomes and, on the other, remittances increase non-farm incomes in Mexico, allowing farm migrants to expand their income portfolio. Hence, these results support the New Economics of Labour Migration (NELM) hypothesis that remittances relax the liquidity constraint in production/investment decisions. Furthermore, family labour availability counterbalances any temporary labour loss because of migration.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".