Environmental Issues in City Logistics: The Case of Low Emission Zones in Europe
Bibliographic record
Abstract
The energy transition can be defined as all the transformations of the system of production, distribution and consumption of energy carried out in a territory in order to make it more ecological. The aim is to reduce the environmental impact of an energy system. Inseparable from sustainable development, the energy transition contributes to the fight against global warming, through the implementation of changes based on innovative technologies, but also and above all on new political orientations. The paper focuses in particular on city logistics in Europe as an illustration of energy transition, showing that strategic interactions between city logistics stakeholders are at the heart of new practices, particularly in the implementation of low emission zones (LEZs). A case study was conducted with a large French metropolitan area, which is at the forefront of sustainable city logistics. This case study is based on an analysis of official documents written as part of the implementation of the LEZ. Using a conceptual framework drawn from the SCP paradigm, which is at the origin of the industrial organization’s stream, the results indicate that the success of environmental city logistics strategies depends effectively on interactions between several public and private stakeholders, and not only on virtuous managerial practices from companies.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".