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Record W1534219926 · doi:10.17226/14609

Practices to Protect Bus Operators from Passenger Assault

2011· book· en· W1534219926 on OpenAlexaboutno aff
Yuko J. Nakanishi, William C. Fleming

Bibliographic record

VenueNational Academies Press eBooks · 2011
Typebook
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsComputer securityBusinessTransport engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

The purpose of this synthesis was to document the state of the practice and report on the practices and policies implemented by transit agencies to deter and mitigate assaults on bus operators. The report incorporates workplace violence issues and up-to-date information on bus operator security measures and practices. The report offers a literature summary of relevant materials; results of a survey distributed to transit agencies in different regions in the United States and Canada; and the results of interviews conducted with key agency personnel. The results of these telephone interviews are presented as profiles with increased coverage of specific security methods and practices used by selected transit agencies. Survey responses from 66 of 88 transit agencies in the United States and Canada, a 75% response rate, are discussed. Twenty-two transit agency profiles offer increased coverage of special security methods or practices of operator security measures used by selected transit agencies, and an appendix of supplemental information contains information about state laws.

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)0.002
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: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.061
GPT teacher head0.274
Teacher spread0.213 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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