Links between production system and transport. The example of German and French industries
Bibliographic record
Abstract
Changes in transportation are closely linked to the economic and logistical characteristics of the production system. The aim of this paper is, on the basis of data on the economic context and surveys conducted in France (the 1988 Shipper survey and the 2004 ECHO survey) and in Germany (the 2005 DLR survey), to show the major changes that have occurred in the two countries at both micro- and macro-economic levels and how these have affected transport demand. \nThe first level of analysis relates to changes in the economic fabric. In particular, we have demonstrated the growing proportion of small and medium-sized firms at a time when large production units, which are those that are best able to concentrate their freight and use modes other than the road, are becoming fewer and fewer. At the same time, economic links are becoming more complex and, in the case of France, we have shown the increasing role played by wholesale traders in the distribution of goods. The constant reduction in transport costs and the opening up of markets is another structural factor whose impacts in both France and Germany we have also analysed. In addition to these economic changes, the internal modes of production of firms have also changed. Production is becoming more diversified and Just-in-time practices are spreading. The fragmentation of freight flows is thus occurring both in space and in time, which also has a major effect on the characteristics of the flows generated by firms and changes in transport. In the case of all these changes we have attempted to show the differences and similarities between the ways transport has changed in the two countries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".