MétaCan
Menu
Back to cohort
Record W91288887

Untersuchung des Einflusses persoenlicher Merkmale auf Testergebnisse in einem Fahranfaengerkurs

2010· article· de· W91288887 on OpenAlexaboutno aff
F Kevins

Bibliographic record

VenueForschungshefte Zweiradsicherheit · 2010
Typearticle
Languagede
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGynecologyArtMedicine
DOInot available

Abstract

fetched live from OpenAlex

Das Basistrainingsprogramm Gearing up (Hochschalten) des kanadischen Sicherheitsrates (Canada Safety Council, CSC) besteht aus einem theoretischen und praktischen Training. Das Kursformat besteht typischerweise aus einem Abend in einem Klassenraum gefolgt von zwei Tagen praktischer Unterweisung an einem Wochenende. Die Teilnehmer muessen eine Vielzahl der Punkte der MOST-II (Motorcycle Operator Skill Test) Fertigkeiten-Evaluation absolvieren, um den Kurs zu bestehen. Gearing Up wird in ganz Kanada und der Provinz Ontario (Bevoelkerung 13 Millionen) angeboten. Ueber 13.000 Teilnehmer nehmen jedes Jahr an diesem Programm teil, das an 25 unterschiedlichen Standorten angeboten wird. In Kanadas Hauptstadt registrieren sich beim Ottawa Safety Council (OSC) jaehrlich ueber 1.000 Teilnehmer an einem der drei Trainingsstandorte. 1998 begann der OSC mit der Erfassung detaillierter Schuelerstatistiken, die Alter, Geschlecht, Vorerfahrung und Testleistung erfassten. Dieser Bericht deckt den Zeitraum von 1999 - 2009 ab, sofern nicht anders angegeben. In einem gegebenen Unterrichtsjahr variiert das Teilnehmeralter von 16 bis 75, mit dem durchschnittlichen Alter, das von 32,6 im Jahr 1999 bis auf 36,5 im Jahr 2009 anstieg. Frauen machten 24,9 Prozent der Schueler von 1999 aus, und ihre Anzahl stieg bis 2009 auf 32,4 Prozent der Eingeschriebenen an. Dieser Bericht untersucht die Testdaten in Bezug auf Fertigkeiten von 9.138 Teilnehmern, um die Auswirkungen von Alter, Geschlecht und Vorerfahrung in Bezug zum Testergebnis setzen. Unter Anerkennung der Tatsache, dass Testergebnisse oft eine Funktion von koerperlicher Muedigkeit oder Lernueberlastung sind, will die Analyse bestimmen, ob alternative Modelle besser fuer eine zunehmend unterschiedliche Teilnehmerpopulation geeignet sein moegen. ABSTRACT IN ENGLISH: The Canada Safety Council (CSC) Gearing Up basic training program consists of theoretical and practical training. The course format is typically one evening in a classroom setting followed by two days of practical instruction over one full weekend. Students must pass a variation of the MOST-II skills evaluation in order to pass the course. Gearing Up is offered across Canada, and in the Province of Ontario (population 13 million) over 13,000 students enroll in the program each year, at one of 25 locations. In Canada's capital, the Ottawa Safety Council (OSC) annually enrolls over 1,000 participants at one of three training sites. In 1998, the OSC began recording detailed student statistics including age, gender, prior experience, and test performance; this paper covers the period 1999-2009, except where noted. In a given teaching year, student age varies from 16 to 75, with the average age increasing from 32.6 in 1999 to 36.5 in 2009; while women represented 24.9 percent of 1999 students, their numbers increased to 32.4 percent of enrollments by 2009. This paper examines the skill test data of 9,138 students to determine the effect of age, gender, and prior experience on test outcome. Recognizing that test outcome is often a function of physical fatigue or learning overload, the objective of the analysis is to determine if alternate delivery models might better suit an increasingly diverse student population. (A) Beitrag zum Themenbereich Fahrer der 8. Internationalen Motorradkonferenz 2010. Siehe auch Gesamtaufnahme der Tagung, ITRD D368201.

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)0.007
metaresearch head score (Gemma)0.046
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 score0.032
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.226
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 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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueForschungshefte ZweiradsicherheitSame topicAgriculture and Farm SafetyFrench-language works237,207