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Record W1586428747 · doi:10.7202/010250ar

Croissance de la population mondiale et environnement : les enjeux

2004· article· fr· W1586428747 on OpenAlexvenueno aff
Thomas Legrand

Bibliographic record

VenueCahiers québécois de démographie · 2004
Typearticle
Languagefr
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

L'auteur passe en revue les effets possibles de la croissance démographique mondiale sur l'environnement et réfléchit sur les décisions politiques qu'ils supposent. Cinq propositions sont au centre de l'exposé. 1) L'évaluation des conséquences environnementales de la croissance démographique doit répondre à des priorités d'ordre éthique. 2) À cause de l'extrême complexité de l'environnement, notre connaissance des déterminants de plusieurs composantes du changement environnemental demeure très limitée. 3) La plus grande partie des effets négatifs de la croissance démographique s'exerce sur les ressources renouvelables plutôt que sur les ressources non renouvelables. 4) Bien qu'elles ne puissent agir que de façon limitée et cumulative sur la taille des populations, les mesures non coercitives de ralentissement de la croissance démographique doivent néanmoins faire partie intégrante d'une panoplie plus large de mesures environnementales. 5) La difficulté de résoudre certains écueils politiques et administratifs occasionnera probablement de sérieux retards dans le développement et la mise en oeuvre de nombreuses politiques non démographiques nécessaires à la prise en charge des enjeux environnementaux planétaires.

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)0.014
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.007
Scholarly communication0.0070.007
Open science0.0020.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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 designNot applicable
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

Citations3
Published2004
Admission routes1
Has abstractyes

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