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Record W2889269673 · doi:10.1051/nss/2018040

Dossier : La fabrique de la compensation écologique : controverses et pratiques – L’économie néo-institutionnelle comme cadre de recherche pour questionner l’efficacité de la compensation écologique

2018· article· fr· W2889269673 on OpenAlexaff
Pierre Scemama, Charlène Kermagoret, Harold Levrel, Anne‐Charlotte Vaissière

Bibliographic record

VenueNatures Sciences Sociétés · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Analyser l’efficacité d’une politique publique implique d’adopter une démarche normative, c’est-à-dire de définir « ce qui doit être » pour ensuite discuter du meilleur chemin pour y arriver. Dans le cadre de la compensation écologique, cet objectif est défini par l’atteinte de l’équivalence entre les pertes liées à un projet et les gains liés aux mesures compensatoires. Cette équivalence repose sur une logique de substitution, qui est au cœur des préoccupations de l’économie de l’environnement. Nous commencerons par présenter les contributions de ce champ théorique à l’étude de l’efficacité de la compensation. Nous en soulignerons aussi les limites, qui nous ont conduits à préférer le cadre de l’économie néo-institutionnelle qui étudie l’efficacité de la compensation comme un problème d’organisation des acteurs en tenant compte de leur contexte institutionnel et environnemental.

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)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.013
Scholarly communication0.0090.012
Open science0.0020.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0230.003

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 head0.119
GPT teacher head0.416
Teacher spread0.297 · 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 designTheoretical or conceptual
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

Citations4
Published2018
Admission routes1
Has abstractyes

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