Urban Transport and Eco-Urbanism: A Global Comparative Study of Cities with a Special Focus on Five Larger Swedish Urban Regions
Bibliographic record
Abstract
Urban transport is critical in shaping the form and function of cities, particularly the level of automobile dependence and sustainability. This paper presents a detailed study of the urban transport eco-urbanism characteristics of the Stockholm, Malmö, Göteborg, Linköping, and Helsingborg urban regions in southern Sweden. It compares these cities to those in the USA, Australia, Canada, and two large wealthy Asian cities (Singapore and Hong Kong). It finds that while density is critical in determining many features of eco-urbanism, especially mobility patterns and particularly how much public transport, walking, and cycling are used, Swedish cities maintain healthy levels of all these more sustainable modes and only moderate levels of car use, while having less than half the density of other European cities. Swedish settlement patterns and urban transport policies mean they also enjoy, globally, the lowest level of transport emissions and transport deaths per capita and similar levels of energy use in private passenger transport as other European cities, and a fraction of that used in lower density North American and Australian cities. Swedish urban public transport systems are generally well provided for and form an integral part of the way their cities function, considering their lower densities. Their use of walking and cycling is high, though not as high as in other European cities and together with public transport cater for nearly 50% of the total daily trip making, compared to auto-dependent regions with between about 75% and 85% car trips. The paper explores these and other patterns in some detail. It provides a clear depiction of the strengths and weaknesses of Swedish cities in urban transport, some key policy directions to improve them and posits possible explanations for some of the atypical patterns observed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".