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Record W2603185683

Transport function vs. post-industrial identities: The urban restructuration of the Rhine river ports (1990-2010)

2013· preprint· en· W2603185683 on OpenAlexaff
Antoine Beyer

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2013
Typepreprint
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsPort (circuit theory)Human settlementUrbanizationService (business)TypologyFunction (biology)Urban planningEconomyBusinessRegional scienceGeographyEconomic geographyCivil engineeringEconomicsEconomic growthEngineering
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.183
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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