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Record W1988672623 · doi:10.3197/096734000129342361

Deforestation, Erosion, and Fire: Degradation Myths in the Environmental History of Madagascar

2000· article· en· W1988672623 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 History · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsMcGill University
FundersU.S. Environmental Protection Agency
KeywordsDeforestation (computer science)Environmental degradationPoliticsRhetoricMythologyPolitical ecologyGeographyBlamePopulationNarrativePovertyPolitical scienceHistoryEcologySociologyLaw

Abstract

fetched live from OpenAlex

Abstract Mention of the island nation of Madagascar conjures up images of exotic nature, rampant deforestation, and destructive erosion. Popular descriptions of the island frequently include phrases such as 'ecological mayhem' or 'barren landscape'. This paper compares this common wisdom and conservation rhetoric about the environmental history of Madagascar with the results of recent research by paleoecologists and others. Deforestation and erosion, while very real trends, are exaggerated due to mistaken ideas about pre-settlement forest extent and the eye-catching red soils and erosion gullies. The role of fire, principal tool of landscape change and pasture maintenance, is unnecessarily demonised. Blame is placed on the Malagasy people and problems of poverty and population growth, ignoring economic interests, historical political contexts, community politics, and the potential of the people to manage their resources positively. Finally, drawing from the recent school of thought that recognises the role of narratives, discourses, and representations in the politics of conservation, this paper concludes by illustrating the political nature of the oft-repeated story of environmental degradation in Madagascar.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.186
Teacher spread0.178 · 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