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Record W4367322667 · doi:10.1111/grow.12678

Developing a typology of daily travelers based on transportation attitudes: Application of latent class analysis using a survey of millennials and older adults in Hamilton, Ontario

2023· article· en· W4367322667 on OpenAlexafffundabout
Shaila Jamal, K. Bruce Newbold, Darren M. Scott

Bibliographic record

VenueGrowth and Change · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLatent class modelTypologyLicensePossession (linguistics)PerceptionTravel behaviorExploratory analysisClass (philosophy)Travel surveyPsychologyGeographyTransport engineeringMarketingAdvertisingBusinessComputer scienceEngineeringStatisticsMathematicsData science

Abstract

fetched live from OpenAlex

Abstract Using survey data of millennials and older adults in Hamilton, Ontario, this exploratory study sought to identify daily travelers based on their attitudes and perceptions toward transportation modes using latent class analysis. Four daily traveler types are identified—“walk and transit‐oriented travelers,” “car‐oriented commuters,” “multimodal travelers,” and “car‐oriented travelers.” The study also examined the association of different sociodemographic characteristics and trip attributes with the four traveler types. Findings suggest that heterogeneity exists within travel‐related attitudes among different traveler types. Further, heterogeneous traveler types exist among individuals belonging to the same generation, with the same living arrangements and possession of a driver's license.

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)0.000
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 score0.449
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.075
GPT teacher head0.317
Teacher spread0.242 · 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

Citations5
Published2023
Admission routes3
Has abstractyes

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