Croissance et répartition en présence d’investissements environnementaux non désirés
Bibliographic record
Abstract
Les politiques de développement durable peuvent avoir, entre autres incidences, celle d’imposer aux firmes des investissements qu’elles n’ont pas désirés. On montre que l’effet le plus à craindre de ce type d’investissement « contraint » n’est pas la dégradation de la rentabilité du capital. Sur ce plan, l’effet (positif) de l’investissement non désiré sur la demande effective compense son effet coût (négatif). Le risque est plutôt celui d’un emballement de la croissance, à cause de la tension créée par le capital improductif sur les capacités de production. Ce risque peut être maîtrisé si les firmes profitent des tensions sur les capacités de production pour augmenter leurs marges. Dans ce scénario le plus vraisemblable, une politique environnementale passant par des investissements non désirés stimule légèrement la croissance, pèse davantage sur la consommation des actionnaires que sur celle des salariés (en parts de PIB) et augmente l’emploi.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".