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Record W2616455531 · doi:10.1093/ajae/aax027

Spatial Patterns of Market Participation and Resource Extraction: Fuelwood Collection in Northern Uganda

2017· article· en· W2616455531 on OpenAlex
Daniela A. Miteva, Randall A. Kramer, Zachary Brown, Martin D. Smith

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Agricultural Economics · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsNickel Institute
FundersInternational Institute for Applied Systems AnalysisNational Science Foundation
KeywordsResource (disambiguation)Natural resourceStock (firearms)Natural resource economicsBusinessEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

Abstract While distance to markets is a key determinant of market participation for households that are dependent on natural resources, the distance to the resource stock is also essential. Thus, a household's location with respect to markets and the resource stock determines household market participation and associated resource degradation. Applying a discrete‐choice framework for fuelwood collection in a developing country, we characterize the spatial pattern of market participation regimes and forest use. All else being equal, autarkic households are closest to the forest and furthest from the market, buyer households are closest to the market and furthest from the forest, and seller households are at intermediate distances. Empirical tests based on survey data from northern Uganda support the predictions from our theoretical model. Our findings have important implications for understanding the spatial patterns of forest degradation and determining the control group when designing impact evaluations of the effectiveness of development and conservation interventions.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.717

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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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