“Old Refineries Rarely Die”: Port City Refineries as Key Nodes in The Global Petroleumscape
Bibliographic record
Abstract
Petroleum and its refined products are globally traded commodities; they are also key elements in our energy landscape and have shaped the built environment in multiple, interconnected ways over the last century. Petroleum flows encompass the entire world. Constellations of oil actors — including corporations and nations — shape seemingly disconnected and geographically distant physical spaces over time. Together, they function as a global palimpsestic petroleumscape. Among the diverse industrial, administrative, retail and ancillary spaces that are part of this petroleumscape, this article argues, refineries have the most important “staying power.” It investigates exemplary cases in four select periods of the petroleum industry: the lighting age (1860s to 1910s), the car age (1910s to 1950s), the plastic age (1950s to 1980s), and the period since the 1980s with its early attempts to go beyond oil. In the first three periods, it explores the relationship between major refineries and nearby (port) cities of Philadelphia, Dunkirk, Suez, Abadan, Rotterdam, and Tehran. It proposes that refineries due to the global networks of petroleum have managed to overcome periods of war and nationalization, of destruction and re-appropriation, while redirecting petroleum flows over time. The article then examines the current state of the refineries discussed in this article, exploring their entanglement with global events and national strategies, and their often detrimental current spatial and environmental impact. The article concludes with a reflection on the necessity to design transition strategies for cities that are based on understanding of the role that refineries have played through time.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".