MétaCan
Menu
Back to cohort
Record W1969480597 · doi:10.1177/154193120905302301

Video Gamer Advantages in a Cellular Telephone and Driving Task

2009· article· en· W1969480597 on OpenAlexafffund
Jason Telner, David L. Wiesenthal, Ellen Bialystok

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2009
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsYork University
FundersYork University
KeywordsTask (project management)Video gameDual (grammatical number)ConversationComputer scienceMultimediaHuman–computer interactionNonverbal communicationPsychologyCognitive psychologyCommunicationEngineering

Abstract

fetched live from OpenAlex

Driving while speaking on a cellular telephone is one of today's most controversial and risky dual task situations. Proficient video game players possess superior divided attention ability and were hypothesized to display superior driving performance compared to non-gamers when engaged in these dual tasks. 115 university students were tested following characterization of their video game proficiency. The driving task, was performed using Drivesim 4.00 software, and was presented by itself as well as in combination with a series of verbal tasks simulating a telephone conversation (the dual task situation). The verbal tasks were also tested apart from the simulated driving. Each participant was thus his/her own control so that the effect of driving or performing verbal tasks could be examined separately and in combination with each other. Compared to non-gamers, proficient video game players had fewer crashes and drove more safely in the dual task conditions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.591

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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.

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

Citations7
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicHuman-Automation Interaction and SafetyFrench-language works237,207