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Protected areas in mainland Southeast Asia, 1973–2005: Continuing trends

2011· article· en· W2131735587 on OpenAlexafffund
Steve Déry, Romain Vanhooren

Bibliographic record

VenueSingapore Journal of Tropical Geography · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsUniversité Laval
FundersSocial Sciences and Humanities Research Council of CanadaUniversité Laval
KeywordsMainlandGeographySoutheast asiaColonialismState (computer science)Environmental protectionEthnic groupEthnologyPolitical scienceArchaeologyHistory

Abstract

fetched live from OpenAlex

Since the 1970s, protected area networks in mainland Southeast Asian countries have developed significantly to occupy 4–25 per cent of their respective national areas, located mostly in the mountainous domains of ethnic minority peoples. Through this process, regions that were only nominally part of national geobodies until the 1950s have become more territorially integrated. The complexity of the characteristics and geographical impacts of this territorialisation have yet to be grasped. As a step in this direction, we briefly outline a multilevel systems approach that usefully contextualizes these issues together with a historical and cartographical assessment of the evolution of protected area networks for Burma, Thailand, Laos, Cambodia and Vietnam. Our main findings are intertwined. On the one hand, protected areas represent a new tool of state intervention in mountainous areas, clearly in keeping with past, notably colonial, actions. On the other hand, this evolution in state territorialisation and attendant power relations have disrupted, far more deeply than previous actions, the pre‐1970s sociogeographical organization in mountainous areas, where most of the region's residual forests remain.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.113
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2011
Admission routes2
Has abstractyes

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