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Record W205400945 · doi:10.4000/vertigo.13589

Les processus de patrimonialisation de la nature dans le Kodagu (Inde) : pluralités, imbrications, contradictions

2013· article· fr· W205400945 on OpenAlexvenueno aff
Béatrice Moppert

Bibliographic record

VenueVertigO · 2013
Typearticle
Languagefr
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Situé dans la partie centrale de la chaîne des Ghâts occidentaux du sud de l’Inde, le Kodagu appartient à l’une de ces 34 régions du globe, identifiées comme points chauds de biodiversité. De fait, les richesses biologiques de ce petit district de l’État du Karnataka sont considérées comme faisant partie de ce bien commun de l’humanité que constitue la biodiversité. La patrimonialisation y apparaît toutefois comme un processus multiforme, révélant de multiples imbrications entre les différents mouvements à l’œuvre. En effet, outre le classement en aires protégées d’une partie de l’espace forestier (parc national, réserve de biosphère, réserves de faune), on assiste à diverses formes de mise en patrimoine où les éléments de nature sont étroitement liés à la culture. Des bois sacrés (devarakadu) aux paysages de la caféiculture, les objets concernés sont de plus en plus nombreux et variés. Portés par des acteurs aux ambitions distinctes, voire contradictoires, ces projets, souvent sources de conflits, sont révélateurs de la pluralité des regards portés sur la nature. En explorant en particulier les enjeux relatifs à la nomination au patrimoine mondial de l’Unesco d’un bien en série réparti le long de la chaîne des Ghâts occidentaux, cet article met en évidence non seulement le manque de concertation, mais aussi l’absence d’une vision territoriale intégratrice dans la mise en œuvre des initiatives de protection et de valorisation des richesses naturelles.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.018
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.217
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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