Des marchandises dans la ville : Un enjeu social, environnemental et économique majeur
Bibliographic record
Abstract
Freight transport and urban logistics are of prime importance. The jobs associated with these activities are very numerous (290,000 in Ile-de-France to which we must add the interim, particularly important) and strategic because they concern people with low and medium school qualifications. The multiplication of logistics centers in the urban peripheries (+ 37% between 2000 and 2012 in Île de France), the explosion of direct deliveries to individuals with the development of e-commerce, up to the demand for 'instant delivery' (the merchandise arrives less than two hours after the order) transform the urban landscape and lifestyles. The economy of digital platforms, supported by start-ups or very large groups, finds one of its privileged fields of development. Despite this high visibility, logistics remains the poor relation of debates and public policies in the metropolises. Cities have little culture of freight transport and use only a modest amount of resources at their disposal. Despite advances in the knowledge of the stakes, despite a high number of strategic programs, our country lacks a solid and realistic corpus of urban transport policies. The subject is treated piecemeal, with regulatory variations according to the communes within the same agglomeration such that they render their respect random and sometimes impossible.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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.
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".