MétaCan
Menu
Back to cohort
Record W4302615482

Keeping waters clean: Environmental Licensing in Rond

2010· article· en· W4302615482 on OpenAlexfundno aff
Andrew Reid Bell

Bibliographic record

VenueDeep Blue (University of Michigan) · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaHorace H. Rackham School of Graduate Studies, University of Michigan
KeywordsEnvironmental scienceEnvironmental chemistryChemistry
DOInot available

Abstract

fetched live from OpenAlex

In the Amazonian agricultural frontier, pasture for cattle is an important and potentially damaging form of land use due to erosion as pastures degrade. This dissertation presents three approaches to understanding policy options to govern this land-use problem: 1) a systems dynamics model (SDM), 2) empirical social research, and 3) an agent-based model (ABM). In the SDM, I examine the role that river basin councils (RBCs) – one of the water governance options in Brazil’s National Water Act – might play in managing this non-point-source pollution issue in the Amazônian State of Rondônia. I compare the central tool of the RBC, a bulk water charge (BWC), to a stylized land-use fine (LUF) for failing to maintain riparian cover, across several scenarios of climate change. The results show no significant advantage to the BWC over LUF in reducing erosion while keeping ranching profitable; moreover, the comparative success of programs similar to LUF suggests these programs may have potential to manage agricultural pollution in the region. One program in Rondônia is the environmental licensing program for rural properties (LAPRO), which requires farms to remove significant amounts of land from production, and may shift production intensity as farms comply. I present empirical data from Rondônia’s Ji-Paraná River Basin that show decreased production intensity and income diversification on larger properties. These results suggest that for smaller properties, complying with LAPRO may bring an increase in land sale to cover debts and an increase in land consolidation in the region. Examining this further, I develop an ABM of ranching and land exchange, inform it with results from my survey research, and investigate the outcomes that could be expected from LAPRO in the context of climate change. Model results show that while LAPRO may increase forest cover in ranching landscapes, it may occur at the expense of the small producer. To the extent that effective monitoring and enforcement exist, a focus on larger holdings will help to mediate this negative social impact. These results suggest that a middle ground may exist in cases where current environmental goals conflict with legacies of past colonization and resource-use regimes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.998

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)0.0030.001

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 head0.003
GPT teacher head0.147
Teacher spread0.144 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueDeep Blue (University of Michigan)Same topicEnvironmental Conservation and ManagementFrench-language works237,207