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Record W2039649489 · doi:10.3402/ijch.v62i3.17563

Determinism, risk and safe driving behavior in northern Alberta, Canada

2003· article· en· W2039649489 on OpenAlexaffabout
J. Peter Rothe, Laureen Elgert

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2003
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDeterminismFatalismFocus groupPoison controlPerceptionPsychologySocial psychologyPublic relationsPolitical scienceMedicineBusinessMarketingEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: There is evidence that Alberta's rural north is over-represented in the Canadian province's overall traffic fatality rate, even after weather, travel exposure and highway geometry are controlled for. OBJECTIVE: The objective of this study was to identify underlying reasons and rationales that northern citizens use to accommodate risk and driving behavior. METHODS: A total of 82 individuals participated in 13 focus groups, each with between 5 and 10 participants. Eight focus groups were conducted with general drivers and five with service professionals in five different Alberta locations. Discussions centered on a series of questions that were designed to elicit insight into general characteristics of the participants' world-view and featured two categories of questions, including dimensions of belief systems and driver characteristics and behavior. RESULTS: Although much of the discussions focused on freedom of choice, over half of the interviewees cited determinism as a key feature of responsibility. Three versions of determinism were emphasized as key in roadway safety: religious determinism, 'universal' determinism (fatalism), and humanistic determinism. These observations highlighted peoples' perception of the likelihood of getting into traffic situations outside one's control. CONCLUSION: In order to maximize the effectiveness of traffic safety in the north, professionals need to take an approach which addresses not only safety issues, but also issues regarding responsibility and its links with behavior.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.027
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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
Published2003
Admission routes2
Has abstractyes

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