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Accidents are Normal and Human Error Does Not Exist: A New Look at the Creation of Occupational Safety

2003· article· en· W1514052693 on OpenAlex
Sidney Dekker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Occupational Safety and Ergonomics · 2003
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsEngineering Link (Canada)
Fundersnot available
KeywordsHuman errorHindsight biasHuman factors and ergonomicsPerspective (graphical)Occupational safety and healthPoison controlAccident (philosophy)Root causeDeviance (statistics)PsychologyObjectivity (philosophy)Risk analysis (engineering)Injury preventionCognitive psychologyForensic engineeringEngineeringComputer scienceOperations managementMedicineEpistemologyMedical emergencyPolitical scienceArtificial intelligenceLaw

Abstract

fetched live from OpenAlex

"Human error" is often cited as cause of occupational mishaps and industrial accidents. Human error, however, can also be seen as an effect (rather than the cause) of trouble deeper inside systems. The latter perspective is called the "new view" in ergonomics today. This paper details some of the antecedents and implications of the old and the new view, indicating that human error is a judgment made in hindsight, whereas actual performance makes sense to workers at the time. Support for the new view is drawn from recent research into accidents as emergent phenomena without clear "root causes;" where deviance has become a generally accepted standard of normal operations; and where organizations reveal "messy interiors" no matter whether they are predisposed to an accident or not.

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.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.383
Teacher spread0.339 · 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