Bibliographic record
Abstract
When forming bicycle infrastructure development programmes, it is necessary to consider the peculiarities of a particular city and the population’s propensity to improve physical and health conditions. It is also essential to explore the possibility of introducing the bicycle into the urban transport system and using it to travel around the city and transport small loads. In most major cities around the world, the objectives of bicycle infrastructure development are often the tasks of easing the traffic load on the road network and reducing traffic congestion. The article aims at analysing the international experience of forming and developing cycling and infrastructure in cities and cycling tourism. The experience of using bicycle traffic most often begins in cities where cycling is very active, among them Amsterdam and Copenhagen. In the Netherlands, the bike has historically been popular due to the frugality of the Dutch, as well as the flat terrain and small size of the country. Amsterdam has brought the bicycle use level in urban travel to 40% of total trips. Montreal is the most bicycle-friendly city in North America. Cars still dominate there, but despite the hilly terrain and cold and snowy winters, the city is actively developing bicycle infrastructure and culture. The programme to bring bicycling back to the streets of Beijing deserves special attention. As recently as 45 years ago, the bicycle was a primary means of transportation in China. In the 1990s, the automobile became a symbol of success and affluence, and city governments began restricting bicycle traffic to allow cars to pass. A 2002 report by the Beijing Institute of Transportation included special measures to limit the use of bicycles and other forms of ‘inadequate transportation’. By 2009, the city banned non-motorised vehicles from 10% of its streets. The document ‘Sustainable Future of Cycling’ in the UK presents the results of the Cycling England programmes, which aim to promote cycling and increase the number of cyclists. There are separate cycling infrastructure development strategies for England, Wales, Scotland, and Northern Ireland. Many cities in Ukraine have developed a concept of bicycle infrastructure development. The main direction is the creation of a complete bicycle infrastructure in cities, which will improve traffic safety, lower traffic jams in large cities, and certainly contribute to reducing hazardous harmful emissions into the air. Keywords: urban planning, transportation, cycling infrastructure, traffic safety, environment, health improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".