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Record W2109146397

Accessibility- vs. Mobility-Enhancing Strategies for Addressing Automobile Dependence in the U.S

2002· article· en· W2109146397 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueeScholarship (California Digital Library) · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsKilometerPopulationAgricultural economicsGeographyGovernment (linguistics)DemographyEconomicsEngineeringTransport engineering
DOInot available

Abstract

fetched live from OpenAlex

Prepared for the European Conference of Ministers of TransportIn 1995, the average American spent 56 minutes a day in a car, a 14 percent increase from only five years earlier. The average American household drove over 33,000 kilometers per year, and the average American car was driven over 19,000 kilometers per year. The growth in total vehicle-kilometers-traveled in the U.S. has continued unabated for decades, far exceeding the growth in population. The U.S. is clearly the most auto-dependent society on earth, but other parts of the world are catching up. By 2000, there were more cars per person in Germany than in the U.S., and nearly as many in Sweden, France, and Canada. The average vehicle in the United Kingdom was driven over 17,000 kilometers per year, just 11 percent behind the average in the U.S. Automobile dependence is growing throughout the world.Growth in automobile travel has been well supported by public investments in roads. Total capital outlays for roads in the U.S. by all levels of government have totaled between $30 billion and $50 billion per year (in constant 2000 dollars) for decades and have approached $60 billion per year in recent years. By 2000, the U.S. had over 3.9 million miles of roads, including over 21,000 miles of freeways in urban areas, and the annual cost of maintaining this system had reached nearly $30 billion per year. From the beginning, the mission of the U.S. Department of Transportation has been to accommodate the growing demand for vehicle travel. Today, the department has established "mobility" as one of its strategic goals and uses trends in vehicle travel as an indicator of progress towards this goal. In its 2001 "Report to the American People," the Federal Highway Administration said, "we must continue to invest in America's highways in order to achieve our national goals".But the investments in roads have not kept up with the growth in vehicle travel. Between 1941 and 2000, total kilometers of roads in the U.S. increased by 145% but vehicle-kilometers-traveled increased by 724%. The gap is significant even when accounting for population growth: kilometers of roads per person increased by 16% while vehicle-kilometers-traveled per person increased by 290% between 1941 and 2000. As demand has outpaced supply, levels of congestion have increased. The Texas Transportation Institute (TTI) calculates that in the 68 largest metropolitan areas in the U.S. the average annual hours of delay per person grew from 11 in 1982 to 36 in 1999, an increase of 227%. The estimated cost of this delay reached $77.8 billion in 1999. How much more road building would it take to eliminate this delay? TTI estimates that metropolitan areas added only 48% of the roads they needed to keep up with the growth in vehicle travel in 1999.At the same time, the environmental consequences of this steady growth in automobile use are well known. Although air quality is better now in places like Los Angeles than it has been in decades, the problem is far from solved. In the U.S., emissions of volatile organic compounds from transportation have been decreasing steadily for the last three decades, but emissions of nitrogen oxides have been going up, and 36 areas that are home to a total of 85 million people still fail to officially meet the national standards for ozone. The transportation sector dumped 513 million metric tons of carbon dioxide, a major greenhouse gas, into the atmosphere in 2000, a 3.43% increase from the year before. In 1999, the U.S. consumed 19.5 million barrels of oil per day, 26.5% of the world's consumption; 68% of oil consumption in the U.S. was for transportation, and consumption of oil in the U.S. for transportation alone exceeded total production of oil in the U.S. by 50%. These statistics and others seem to provide ample justification for policies to reduce automobile use.That leads to something of a dilemma for policy makers. Should policies focus on accommodating growing levels of vehicle travel because driving more is apparently what the public wants to do? Or should policies focus on limiting driving so as to reduce environmental and other costs? The former strategy has so far been more politically palatable, at least in the U.S., but it is also becoming increasingly unaffordable. The latter strategy means reversing a trend that has slowed only for wars and recessions and goes against American traditions of freedom of movement. So what's the right thing to do? One obvious approach is to push for further improvements in vehicle and fuel technologies that will reduce the environmental impacts of driving without in anyway limiting driving. But that leaves the problem that driving is growing faster than capacity possibly can. It also leaves the problem that a significant share of the population cannot drive or does not have access to a car, for reasons of income, age, or ability. An alternative approach that is gaining wide support in the U.S. is to reduce the need for driving by bringing activities closer to home, by improving the quality of transit, bicycling, and walking – by enhancing accessibility. Such an approach represents a fundamental shift from a traditional focus on enhancing mobility through road building. This report looks at what it means to focus on enhancing accessibility rather than enhancing mobility, first by defining these concepts then by reviewing the U.S. experience with mobility-enhancing strategies, accessibility-enhancing strategies, and others.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0050.013
Open science0.0020.000
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 head0.045
GPT teacher head0.291
Teacher spread0.246 · 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