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Record W3125224897 · doi:10.1017/s1355770x08004415

A spatiotemporal model of shifting cultivation and forest cover dynamics

2008· article· en· W3125224897 on OpenAlex

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

VenueEnvironment and Development Economics · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsWorld Wildlife Fund Canada
Fundersnot available
KeywordsResource (disambiguation)Shifting cultivationDependency (UML)Stock (firearms)AgroforestryEnvironmental resource managementForest coverAgricultureEnvironmental scienceGeographyEcologyComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Sustainable use of humid forest resources as a source of fertile land for cultivation requires long periods of fallow and the ability to move the zone of active cultivation from one location to another over time. At the individual field level, shifting cultivation is essentially a resource extraction problem akin to a pulse fishery – a short period of intensive use of the stock of soil fertility followed by a long idle period permitting regeneration. This paper describes a spatiotemporal model of resource extraction adapted to the use of forest resources by shifting cultivators. Theoretically grounded in the spatial and household modelling literature, it is a structural simulation model of household decision-making, and includes a demonstration of the concept with a limited data set from southern Cameroon. Use of a stated preference approach to modelling decision-making identifies individual preferences and spatial path-dependency as important sources of shortened fallows and resource degradation.

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 score0.101
Threshold uncertainty score0.424

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 head0.019
GPT teacher head0.153
Teacher spread0.134 · 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