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Record W2899492090 · doi:10.7201/earn.2006.12.06

Pobreza, degradación ambiental y liberalización del comercio: Hacia una intervención de políticas «second best»

2011· article· en· W2899492090 on OpenAlexaff
Unai Pascual, Roberto Martı́nez-Espiñeira

Bibliographic record

VenueEconomía Agraria y Recursos Naturales · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Innovation
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsSubsidyAgricultureEconomicsPovertyIntervention (counseling)GeographyNatural resource economicsWelfare economicsEconomic growth

Abstract

fetched live from OpenAlex

<span>Forest based agricultural systems in the tropics are being opened up to international trade at an unprecedented rate.This is the case of tropical agriculture in Mexico under the North American Free Trade Agreement (NAFTA), which is also having significant impacts on the decentralized land use decisions of small-scale farmers and on the natural resource base on which they depend. This paper develops a bioeconomic model of a typical forest-land based farming system that is integrated with the non-farm labour sector, as typically found in tropical regions. The data used to generate the simulations were gathered in two communities of Yucatan (Mexico) in 1998-2000. Through a systemdynamics framework, the agro-ecological and farming economic subsystems are integrated and the current situation of price liberalization that is negatively affecting soil capital and income levels is compared to a scenario that precludes an «optimal path to extinction» through careful policy intervention. This second-best case is based on a targeted policy mix that seeks to maintain the system viable for as long as possible above an irreducible poverty level. The policy intervention involves, simultaneoulsy, subsidizing off-farm wage rates, intensification of land use, and the control of households’ rights to the forest commons. The model shows that such policy intervention can result in a large positive discounted net payoff basedon the increased incomes for the farming community after deducting the implementation costs of such intervention.</span>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.062
GPT teacher head0.310
Teacher spread0.248 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2011
Admission routes1
Has abstractyes

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