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Record W4404907963 · doi:10.4000/12tal

Controverses environnementales sur la gestion d’espaces naturels protégés : le cas de zones humides littorales atlantiques françaises

2024· article· fr· W4404907963 on OpenAlexvenueno aff
Léa Paly, Nathalie Carcaud, Véronique Beaujouan

Bibliographic record

VenueVertigO · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsForestryGeography

Abstract

fetched live from OpenAlex

Les zones humides littorales ont fait l’objet de changements importants dans l’ouest de la France en particulier depuis le XVIIIe siècle et connaissent aujourd’hui des processus de protection de leur caractère naturel. Cet article, issu d’une recherche doctorale, interroge les patrimoines naturels de trois zones humides littorales atlantiques dans un contexte de changements globaux. La lecture des documents de gestion et la réalisation d’une enquête qualitative composée de 27 entretiens auprès des acteurs de la protection de la nature et des usagers des sites montrent dans un premier temps que ces patrimoines protégés sont issus de la convergence de réalités écologiques, politiques et sociales. Ces patrimoines sont aujourd’hui reconnus et appropriés par les gestionnaires et usagers. Dans un second temps, l’analyse des entretiens met en lumière différentes visions portées sur ces paysages et révèle des controverses quant au choix des états de référence de ces espaces naturels protégés et de leur évolution future. Ces controverses puisent leur origine dans la pluralité des représentations sociales de la nature entre usagers et gestionnaires, dans l’influence des paradigmes autour de la protection des milieux naturels, et de l’histoire environnementale des sites étudiés.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.180
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0070.012
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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Same venueVertigOSame topicFrench Urban and Social StudiesFrench-language works237,207