La fiscalité carbone en France : un échec face à la Suède ? Le cas des transports routiers de marchandises
Bibliographic record
Abstract
Inseree au sein du projet de loi de finances (PLF) francais 2010 sous la forme d'une Contribution Climat-Energie (CCE), la taxe carbone en fut ensuite retiree. Sans s'attarder sur les raisons politiques de ce retrait, c'est sur l'efficacite qu'elle aurait pu avoir tant sur le plan ecologique qu'economique que nous nous interrogeons. Prenant l'exemple du transport routier de marchandises (TRM) specifiquement vise par la loi, nous nous referons aux previsions des experts (via differentes simulations realisees a partir des modeles macroeconomiques, ou les preconisations de la commission Rocard), et aux discours des acteurs francais concernes (chargeurs, transporteurs, federations,~). La taxe carbone si majoritairement rejetee par ces derniers au nom d'une atteinte de leur competitivite et d'une surfiscalisation du secteur a t-elle ete abrogee a bon escient ?
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
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".