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Record W2058183620 · doi:10.1002/atr.5670350304

Fare deregulation of transit services: Winners and losers in a competitive market

2001· article· en· W2058183620 on OpenAlexvenueno aff
Hong K. Lo, C. W. Yip

Bibliographic record

VenueJournal of Advanced Transportation · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsDeregulationRevenueBusinessGovernment (linguistics)Public transportService (business)Transit (satellite)Control (management)Transport engineeringIndustrial organizationPublic economicsFinanceEconomicsMarketingMarket economyEngineering

Abstract

fetched live from OpenAlex

Abstract Currently, the Hong Kong government imposes fare control on buses and taxi while the rail services are immune to such a control. This study examined four scenarios of fare deregulation on transit services by considering three related parties of a transit system – service providers, travelers, and society in general, with their respective objectives represented as – revenue, travel utility, and congestion. Analyzing the resultant impacts on these three parties, we found that a different regulatory environment would favor or hurt a different set of parties. There is no clear win‐win situation for all parties. Deciding a socially acceptable regulatory environment is likely to involve difficult tradeoffs among these parties.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.308

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 communication0.0000.001
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 head0.007
GPT teacher head0.259
Teacher spread0.252 · 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

Citations11
Published2001
Admission routes1
Has abstractyes

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