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Record W2765472270 · doi:10.5070/bp321112726

Travel Behavior of Mexican and Other Immigrant Groups in California

2008· article· en· W2765472270 on OpenAlexaboutno aff
Susan Handy, Evelyn Blumenberg, Moria Donahue, Kristin Lovejoy, Caroline Rodier, Susan Shaheen, Kimiko Shiki, Lily Song

Bibliographic record

VenueBerkeley Planning Journal · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationQuarter (Canadian coin)PopulationEconomic growthSociologyGeographyEconomicsDemography

Abstract

fetched live from OpenAlex

California is the destination for over one-quarter of immigrants to the United States, and immigrants now make up over one-quarter of the state's population. To ensure that transportation systems and services adequately meet the needs of recent immigrants, planners need a firm understanding of the travel behavior of immigrant groups. This paper reports on key findings from a three-phased study:(1)analysisofdataoncommutetravelofCaliforniaimmigrants from the 1980, 1990, and 2000 Censuses; (2) focus groups with recent Mexican immigrants on their transportation experiences and needs in six California regions; and (3) interviews with community-based organizations in nine California regions on the transportation needs and wants of Mexican immigrants. These findings point to a long list of potential strategies for agencies and organizations to consider in efforts to more effectively meet the transportation needs of Mexican and other immigrants in California.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.311
Threshold uncertainty score0.618

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.309
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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

Citations19
Published2008
Admission routes1
Has abstractyes

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