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Record W7130313310 · doi:10.5281/zenodo.18682969

URBAN TRANSPORT AND RADICAL GEOGRAPHY: RECONFIGURING BERLIN'S LOGISTICS IN THE GLOBAL CAPITALIST SYSTEM

2025· article· en· W7130313310 on OpenAlexaff
Nathaniel James Rowland

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsQueen's University
Fundersnot available
KeywordsCirculation (fluid dynamics)State (computer science)Power (physics)Space (punctuation)CommodificationMaterialismIntervention (counseling)BoomEmbodied cognition

Abstract

fetched live from OpenAlex

Highways are vital to global supply chains, enabling the dominant form of circulating goods inland by truck. Within critical economic geography and related disciplines, however, insufficient attention has been placed on developing a radical highway geography that positions highways within the evolving relationships between global capital, state scales and the labour of moving goods. I fill this silence by applying a historical-geographical materialist lens to Germany’s most congested, costly, and controversial highway – Berlin’s intercity A100 – to explore the entanglements of highways, labour power and the capitalist state within the socio-spatial and temporal dynamics of global capitalism. By following the A100 from the 1950s to the proposed completion of its contentious 16th extension in 2025, I argue that the 16th construction phase is the outcome of continual attempts by the capitalist state – at various scales of intervention – to annihilate space through time. These time–space compressions, which are incomplete, contradictory and contested, facilitate the circulation of commodities – understood here as urban freight and labour power – across space more rapidly and at lower cost, leading not only to a remaking of city logistics but also in the embodied labour of truck drivers, whose working lives increasingly reflect the pressures of accelerated circulation

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicWater Governance and InfrastructureFrench-language works237,207