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Record W3123424117

Get on the Bus

2008· preprint· en· W3123424117 on OpenAlexaboutno aff
Cheryl Brown

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldSocial Sciences
TopicPublic Spaces through Art
Canadian institutionsnot available
Fundersnot available
KeywordsPublic transportTransit (satellite)Investment (military)Traffic congestionAdministration (probate law)BusinessDependency (UML)Political scienceEconomic growthPublic administrationTransport engineeringEngineeringEconomicsPolitics
DOInot available

Abstract

fetched live from OpenAlex

In this article, the author conducted preliminary research on public transportation systems in four countries to aid in the development of a Comparative Public Administration course. The four countries (Canada, Mexico, the United Kingdom and South Africa) each offer unique challenges regarding mass transit. Increasing investment in mass public transit is vital to controlling urban pollution, reducing dependency on foreign oil, and reducing traffic congestion. Additionally, the article looks at the use of sabbaticals as a tool for researchers, both as a method for revitalizing professionals in the academic world and as a way to encourage research on subjects which may be less well-funded. The research will be incorporated into the course as an example of the kinds of research the students can do themselves, regardless of area of interest.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
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 head0.072
GPT teacher head0.373
Teacher spread0.301 · 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
Published2008
Admission routes1
Has abstractyes

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