Transport function vs. post-industrial identities: The urban restructuration of the Rhine river ports (1990-2010)
Bibliographic record
Abstract
In the last two decades most of the German ports, but also Strasbourg (F) and Basel (CH), are on the way or have already developed impressive urban waterfronts projects. They usually followed models adopted by numerous sea ports from the 70ies on. Thus, urban authorities consider the port areas as underused and sometime merely as wasteland. Their claims for urbanizing river banks are part of a global strategy were the Rhine metropolis have to compensate the decline of manufacturing industries and to shape an urban image that fits to service economy in order to attract people and high skilled activities. New urban settlements along the Rhine show great architectural ambitions that are also part of a globalized city marketing (i.e Duisburg, Düsseldorf or Cologne). On the other hand, global economy needs unprecedented transport capacities by river. The continuous shit of container traffics to the hinterland is supposed to double till 2020. But this demand could be threatened by shrinking land availability for port installations. In these controversial positions presented by a large literature review, the first objective of our paper is to establish a survey of land consumption for port or urbanization purposes. The first objective is to see in what extend port areas have really shrinked (in absolute and in relative value) during the last 15 years). The second objective is to set up a typology presenting the several development paths followed by the several cities along the Rhine. The research will be set on the detailed analysis of variables that could explain the differences (proximity to the inner city, to the sea ports, the size of the port, but also historical specialization and political decision making).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".