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Record W3196433502 · doi:10.1051/cagri/2021015

Oil palm cultivation in the Americas: review of the social, economic and environmental conditions of its expansion

2021· article· en· W3196433502 on OpenAlexaff
Colombine Lesage, Jaime Andrés Cifuentes-Espinosa, Laurène Feintrenie

Bibliographic record

VenueCahiers Agricultures · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsSustainabilityPalm oilProduction (economics)CertificationBusinessPrivate sectorAgriculturePalmElaeis guineensisContract farmingSustainable developmentAgricultural economicsNatural resource economicsAgricultural scienceEconomic growthEconomicsGeographyPolitical scienceBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.234
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2021
Admission routes1
Has abstractyes

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