Oil palm cultivation in the Americas: review of the social, economic and environmental conditions of its expansion
Bibliographic record
Abstract
In the Americas, the palm oil sector has been gaining importance in the last 20 years. Although in 2018 the region only accounted for 7.1% of global palm oil production, it is one of the largest suitable areas for oil palm cultivation. We conducted a literature review on how the sector developed and how its development influenced private and public actors in their choice among three categories of arrangements between oil palm growers and palm oil extraction units. We grouped cases reported in the literature in three categories: corporate models, contract farming, and growers’ organizations. The two latter categories emerged in response to the call for better inclusion of growers in the value chain, for local development, and for sustainable production; they now represent almost 30% of production in the region. All the parties involved are pushing for more sustainable production. National governments intend to regulate production, and private companies are engaging in certification and fair partnerships with producers of fruit bunches. However, there are still many negative impacts on the environment, on local populations, and on biodiversity. Thus, although the Americas appear to be on the way to being leaders of sustainability in the palm oil sector, challenges remain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".