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Record W653783818

Fahrer ohne Fuehrerschein: Wie gross ist das Problem und wie kann damit umgegangen werden? - Ein internationaler Blick

2007· article· de· W653783818 on OpenAlexaboutno aff
B M Sweedler, K Stewart

Bibliographic record

VenueSCHRIFTENREIHE FAHREIGNUNG · 2007
Typearticle
Languagede
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGynecologyArtMedicine
DOInot available

Abstract

fetched live from OpenAlex

Der vorliegende Beitrag diskutiert das Problem des Fahrens ohne Fuehrerschein. Es gibt einerseits jene Fahrer, die nie einen Fuehrerschein erworben haben, und jene Fahrer, deren Fuehrerschein ungueltig ist. Es gibt Untersuchungen aus verschiedenen Laendern. Eine Befragung in den USA ergab, dass in ein Fuenftel aller toedlichen Unfaelle Fahrer involviert sind, die keinen Fuehrerschein hatten. Eine in Queensland, Australien, durchgefuehrte Untersuchung ergab, dass 7,9 Prozent der Fahrer, die in toedliche Unfaelle verwickelt waren, keinen gueltigen Fuehrerschein hatten. In der kanadischen Provinz Ontario entfaellt einer von 14 toedlichen Unfaellen auf Fahrer ohne Fuehrerschein. Auch in europaeischen Laendern weisen Fahrer ohne Fuehrerschein ein hoeheres Unfallrisiko auf. So sind zum Beispiel laut einer im Jahr 2004 durchgefuehrten Studie des Verkehrsministeriums auf den Strassen des Vereinigten Koenigreichs rund eine Million Fahrer ohne Fuehrerschein unterwegs. In Belgien wurden im Jahr 2005 5.953 Fahrer bestraft, die keine Fahrerlaubnis besassen, und 803, denen der Fuehrerschein entzogen worden war. Trotz der hohen Beteiligung an toedlichen Unfaellen wird das Problem des Fahrens ohne Fuehrerschein oft nicht ernst genug genommen. Es besteht zudem die Gefahr, dass das Fuehrerscheinsystem unterlaufen wird und der Fuehrerscheinentzug als Strafmassnahme entwertet wird. Die Empfehlungen, die in Studien aus den USA, dem Vereinigten Koenigreich und Australien erarbeitet wurden, werden vorgestellt. Die Vorschlaege reichen von hoeheren Strafen bis zu Kennzeichenentzug und Fahrzeugbeschlagnahmung. Zur Gesamtaufnahme siehe ITRD D361720. (KfV/A) ABSTRACT IN ENGLISH: The problem of unlicensed drivers is a major road safety problem in countries around the world. A survey in the U.S. showed that 20 percent of all fatal crashes in the U.S. involved drivers, who were unlicensed. A study in Queensland, Australia showed that unlicensed drivers represented 7.9 percent of drivers involved in fatal crashes. In Ontario, one in fourteen fatal crashes involved an unlicensed driver. European countries have also found that unlicensed drivers pose a higher risk. A 2004 U.K. Department for Transport report found that there are around one million unlicensed drivers on U.K roads. The report notes that while unlicensed drivers account for less than one percent of total hours driven, unlicensed drivers are up to nine times more likely to have an accident than licensed drivers. Despite the marked over-involvement of improperly licensed drivers in fatal crashes, violations are often not treated seriously. The presentation session discusses the worldwide scope of the problem and potential solutions, including the impoundment of the vehicles of those who are driving illegally. (A)

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.004
Scholarly communication0.0070.008
Open science0.0020.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0260.004

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 head0.011
GPT teacher head0.268
Teacher spread0.258 · 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
Published2007
Admission routes1
Has abstractyes

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