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Record W2064287878 · doi:10.1109/icpim.2011.5983633

Research on promoting transportation administrative law enforcement team building

2011· article· en· W2064287878 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTechnology and Security Systems
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsLaw enforcementChinaEnforcementBusinessAdministrative lawFace (sociological concept)Tax lawTransport engineeringPublic administrationLawPolitical scienceFinanceEngineeringSociologyDouble taxation

Abstract

fetched live from OpenAlex

With the arrival of the critical period of reform and development, profound changes are taking place in economic system, social institutions, the pattern of interests and ideas in China. Facing the new and complex situation, particularly the impact on the transport brought by the oil price and tax reform, law enforcement agencies, personnel, funding channels, and development pattern in transportation chief law enforcement ranks also face unprecedented opportunities and challenges. Based on the national survey results, this essay will introduce the construction situation and status of traffic law enforcement in China, deeply analyze and reflect the main problems and causes, and put out ideas for our future transport administrative law enforcement team building through specific measures and suggestions.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.002
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.166
GPT teacher head0.377
Teacher spread0.211 · 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 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
Published2011
Admission routes1
Has abstractyes

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