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Record W621982874

Inside Man: TransLink's New Top Guy, Ian Jarvis, Has Seen the Agency Grow from Its Infancy to a Pacific Coast Powerhouse

2010· article· en· W621982874 on OpenAlexaboutno aff
Fred E. Jandt

Bibliographic record

VenueMass transit · 2010
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Transit (satellite)PaymentRevenueService (business)TourismBusinessPublic transportEngineeringTransport engineeringGeographyMarketingFinanceSociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Vancouver’s TransLink and its new director Ian Jarvis are topics of this story. The article ranges from a look at Jarvis’ beginning as an accountant for TransLink to the transit agency’s expansion since it was created in 1999 and the effects of the 2010 Winter Olympics. Jarvis describes multiple reasons for TransLink’s success: its payment system, ridership and revenue, transit coordination as it relates to land-use, and the agency’s emphasis on customer service. During the influx of visitors for the Olympics, Jarvis admits the system was stretched the first few days, and queue management became integral. Overall ridership remained up following the Olympic games.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.023
GPT teacher head0.191
Teacher spread0.169 · 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.

Study designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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