Ports, Cities, and Global Supply Chains
Bibliographic record
Abstract
Contents: Introduction, James Wang, Daniel Olivier, Theo Notteboom and Brian Slack. Part 1 Conceptualization of Port-Cities and Global Supply Chains: Supply chain and supply chain management: appropriate concepts for maritime studies, Valentina Carbone and Elisabeth Gouvernal Global supply chain integration and competitiveness of port terminals, Photis M. Panayides The terminalisation of seaports, Brian Slack Re-assessing port-hinterland relationships in the context of global supply chains, Theo Notteboom and Jean-Paul Rodrigue. Part 2 Shipping Networks and Port Development: The development of global container transhipment terminals, Alfred J. Baird Mediterranean ports in the global network: how to make the hub and spoke paradigm sustainable?, Enrico Musso and Francesco Parola Northern European range: shipping line concentration and port hierarchy, Antoine Fremont and Martin Soppe Factors influencing the landward movement of containers: the cases of Halifax and Vancouver, Robert J. McCalla. Part 3 Inserting Port-Cities into Global Supply Chains: Globalization and the port-urban interface: conflicts and opportunities, Yehuda Hayuth A metageography of port-city relationships, Cesar Ducruet Chinese port-cities in the global supply chains, James Wang and Daniel Olivier The economic performance of seaport regions, Peter W. De Langen. Part 4 Corporate Perspectives on the Insertion of Ports in Global Supply Chains: The success of Asian container port operators: the role of information technology, Daniel Olivier and Francesco Parola Which link in which chain? Inserting Durban into global automotive supply chains, Peter V. Hall and Glen Robbins Sustainable development and corporate strategies of the maritime industry, Claude Comtois and Brian Slack References Index.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.002 |
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".