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Record W629281114

Women in Transportation [2008]

2008· article· en· W629281114 on OpenAlexaboutno aff
Kristen Force, Camella Lobo, Joan Shim, Nicole Schlosser

Bibliographic record

VenueMetrologia · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsManagementMetropolitan areaTransit (satellite)NegotiationOfficerChief executive officerVice presidentExecutive directorWifePublic transportPolitical sciencePublic administrationSociologyHistoryLawArchaeologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

This article presents profiles of ten women in transportation who have used their skills in finance, construction, civic involvement, contract negotiations, planning, social activism and entrepreneurship to make significant contributions to the transit industry. The women include: 1) Linda Bohlinger, Vice President and and Director of National Management Consulting at HNTB Corp., Santa Ana, CA; 2) Flora Castillo, Member of the Board at New Jersey Transit (NJ Transit); 3) Dorothy Dugger, General Manger of San Francisco Bay Area Rapid Transit (BART); 4) Angela Iannuzziello, President of ENTRA Consultants in Toronto; 5) Carol Inge, Chief Planning Officer at Los Angeles County Metropolitan Transportation Authority; 6) Diane James, Executive Director of Women's Transportation Seminar; 7) Marcia Milton, President and CEO of First Priority Trailways, District Heights, MD; 8) Heather Rachels, Program Manager for Meetings and Conventions at American Public Transportation Association (APTA); 9) Janet Rogers, Vice President of Engineering at Stacy and Witbeck Inc., Alameda, CA; and, 10) Kim Turner, Transit Director at Torrance Transit, Torrance, CA.

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 score0.031
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.195
Teacher spread0.171 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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