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Record W2433444342 · doi:10.1123/jpah.2014-0052

Walk, Bicycle, and Transit Trips of Transit-Dependent and Choice Riders in the 2009 United States National Household Travel Survey

2014· article· en· W2433444342 on OpenAlexaff
Ugo Lachapelle

Bibliographic record

VenueJournal of Physical Activity and Health · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsTRIPS architecturePublic transportTypologyTransport engineeringTransit (satellite)BusinessTravel behaviorTrip generationTelephone surveyVehicle miles of travelAdvertisingGeographyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Previous research has shown that public transit use may be associated with active transportation. Access to a car may influence active transportation of transit riders. METHODS: Using the 2009 United States National Household Travel Survey (NHTS), transit users ≥ 16 years old (n = 25,550) were categorized according to driver status and number of cars and drivers in the household. This typology ranged from choice transit riders (ie, "fully motorized drivers") to transit-dependent riders (ie, "unmotorized nondriver"). Transit trips, walking trips, and bicycling trips of transit users are estimated in negative binomial models against the car availability typology. RESULTS: Sixteen percent of participants took transit in the past month; most (86%) lived in car-owning households. As income increased, car availability also increased. Transit user groups with lower car availability were generally more likely than fully motorized drivers to take more public transit, walking, and bicycle trips. Transit riders have varying levels of vehicle access; their use of combinations of alternative modes of transportation fluctuates accordingly. Transit-dependent individuals without cars or sharing cars used active transportation more frequently than car owners. CONCLUSION: Policies to reduce vehicle ownership in households may enable increases in the use of alternative modes of transportation for transit users, even when cars are still owned.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.000
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 head0.084
GPT teacher head0.358
Teacher spread0.274 · 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

Citations27
Published2014
Admission routes1
Has abstractyes

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