The Global Production of Transportation Public–Private Partnerships
Bibliographic record
Abstract
Abstract Around the world, public–private partnerships have become increasingly popular to deliver large‐scale transportation infrastructure projects such as roads, bridges, railways, subways, seaports and airports. The aim of this article is to provide a framework to understand the global geography of projects built through this market‐driven procurement model, which have been predominantly concentrated in a small number of developed countries and emerging markets. As is shown, within many countries, a governance and regulatory environment has been established that supports public–private partnerships over other alternative procurement approaches. Nevertheless, the production of public–private partnerships worldwide has been dominated by a relatively small number of highly globalized construction contractors, engineering firms, financiers, accountancies and consultants from developed countries, who have focused their activities in a narrow set of regions. The article concludes by reflecting on the implications of the high level of industry concentration, and emerging trends showing greater involvement from firms from developing countries. Resumé À travers le monde, les partenariats public‐privé sont de plus en plus utilisés pour les projets d’infrastructure de transports de grande envergure, tels que routes, ponts, voies ferrées, métros, ports et aéroports. Cet article définit un cadre permettant de comprendre la géographie planétaire des projets bâtis selon ce modèle orienté par le marché, projets concentrés dans un petit nombre de pays développés et émergents. Les régimes de gouvernance et la réglementation mis en place dans de nombreux pays favorisent les partenariats public‐privé au détriment d’autres approches de réalisation de projets. Néanmoins, la production de ces partenariats dans le monde a été dominée par un nombre relativement réduit d’entreprises de bâtiment et d’ingénierie, de bailleurs de fonds, de cabinets de comptabilité et de conseils, acteurs installés dans des pays développés et dont les activités internationalisées s’exercent sur un ensemble restreint de régions. La conclusion aborde les conséquences d’une forte concentration industrielle et l’apparition d’une implication croissante des entreprises des pays en développement.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| 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".