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Record W6980027414

Are Britain’s railways costing too much? Perspectives
\nbased on TFP comparisons with British Rail 1963–2002

2006· article· en· W6980027414 on OpenAlexaboutno aff

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsActivity-based costingCashQuality (philosophy)ProductivityQuarter (Canadian coin)Force majeureTotal factor productivityQuality costsLife cycle costingCost analysis
DOInot available

Abstract

fetched live from OpenAlex

Following the Hatfield accident in October 2000, the cost of running Britain’s railways has \nincreased very sharply, leading to considerable debate about whether current cost levels are \nreasonable. This paper seeks to inform this debate by assessing post-Hatfield cost and TFP \nlevels against the historical precedents set by British Rail and the early experience of the \nnewly privatised industry. The results show that industry cash costs rose by 47 per cent \nbetween 1999/2000, the last financial year before Hatfield, and 2001/2002 — but, \nsurprisingly, with train operating costs accounting for 42 per cent of this growth. The \nresults also show that the post-Hatfield cost spike is unprecedented when compared \nagainst historical benchmarks. Analysis of long-term data on quality and safety measures \nindicates that an excessive focus on rail safety may offer part of the explanation for the \ncost growth.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.368
Threshold uncertainty score0.732

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.036
GPT teacher head0.210
Teacher spread0.174 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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