Cited by 60Conservation, Biodiversity, and Resource ManagementLand Rights and ReformsAgriculture, Land Use, Rural Development

Land grabbing in the Brazilian Amazon: Stealing public land with government approval

Carrero, Gabriel Cardoso, Walker, Robert Tovey, Simmons, Cynthia Suzanne, Fearnside, Philip Martin·2022·Land Use Policy

Integrity signals

Registry

Crossref · 10.1016/j.landusepol.2022.106133

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

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Claims other papers make about this one

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Cites

Flagged first, then by citations

Authors
Carrero, G. C., Walker, R. T., Simmons, C. S., & Fearnside, P. M.
Affiliations
  • University of Florida (US)
  • Instituto Nacional de Pesquisas da Amazônia (BR)
Corresponding author
Carrero, Gabriel Cardoso
Venue
Land Use Policy
Publisher
Elsevier BV
Published
2022-09
Volume
120
Pages
106133
ISSN
0264-8377 (ISSN-L)
OpenAlex
W4225284464
Cited by
60
References
1
Citations by year
2026: 11 · 2025: 18 · 2024: 17 · 2023: 13 · 2022: 1
FWCI
4.67
Type
journal article
Language
en
Open access
closed
Locations
  • Land Use Policy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • Gordon and Betty Moore Foundation
  • University of Florida
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Conservation, Biodiversity, and Resource Management
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Land Rights and Reforms
  • Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agriculture, Land Use, Rural Development
Keywords
land grabbing, Brazilian Amazon, deforestation, protected areas, land law reform, land legalization, commodity supply chains, Amazon frontier

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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