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Record W103308084

STRADA - THE WORLD'S NEWEST BUS OPERATOR SELECTION TOOLKIT

2011· article· en· W103308084 on OpenAlexaboutno aff
Michael W. Roschlau

Bibliographic record

VenueCONGRESS - DUBAI 2011 · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsSuiteProcess (computing)AttendanceTest (biology)Product (mathematics)Presentation (obstetrics)Strengths and weaknessesSelection (genetic algorithm)EngineeringOperations researchComputer scienceProcess managementKnowledge managementMarketingEngineering managementBusinessPsychologyGeographyPolitical scienceArtificial intelligenceMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

STRADA is a new bus driver screening and selection tool that has significantly improved the suitability of candidates, streamlined the recruitment process and reduced training attrition at Canadian public transport systems. STRADA consists of a six-step process to identify the best-fit for the position of bus driver. The core of the program is an online psychometric evaluation test based on 25 years of research in 42 countries and 16 languages. The test identifies a candidate’s strengths and weaknesses in areas such as attendance, ability to relate to management, independence, problem solving, concern for safety, customer service, and many others. STRADA’s suite of assessments provide an holistic picture of a candidate to assist in making the right hiring decision, saving public transport systems money and time by reducing issues with employees. This presentation offers an overview of the product development, how the four issues are addressed, the six competencies that make up the test, as well as explaining how results are tabulated and individual reports and interview frameworks and produced

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.285
Teacher spread0.242 · 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 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
Published2011
Admission routes1
Has abstractyes

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