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Record W1970478488 · doi:10.1504/ijtpm.2005.007520

Exchanging experiences in transport infrastructure policies between Denmark and the Netherlands

2005· article· en· W1970478488 on OpenAlexaff
Martin de Jong, Harry Geerlings

Bibliographic record

VenueInternational Journal of Technology Policy and Management · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsBenchmarkingTransport policyBusinessPublic economicsField (mathematics)Cultural exchangeTransport infrastructurePolitical scienceEconomicsMarketingSociologyPublic transportLawTransport engineeringEngineering

Abstract

fetched live from OpenAlex

Under the influence of international benchmarking processes, attention paid to cross national, lesson drawing has risen substantially. It is often believed, and for good reasons, that transplantation of policy models between countries with similar legal, cultural and institutional characteristics, is easier. Though this may be true, spotting subtle institutional differences and practical policy problems on the side of the receiving country are keys to success. In this paper, it is claimed that Denmark and the Netherlands share quite a few important characteristics in the field of transport infrastructure policies, institutional as well as regarding citizen and policy preferences, making mutual exchange of experiences, promising. In addition, the Denmark-Holland comparison and inventory of exchange options serves as a stepping stone to conduct similar comparisons with other countries not studied here.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0090.005
Open science0.0010.006
Research integrity0.0020.002
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 head0.010
GPT teacher head0.301
Teacher spread0.291 · 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 designQualitative
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

Citations12
Published2005
Admission routes1
Has abstractyes

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