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Record W2909083472 · doi:10.1080/24725838.2018.1560927

Ergonomics and Human Factors in Healthcare System Design – An Introduction to This Special Issue

2018· article· en· W2909083472 on OpenAlex

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

VenueIISE Transactions on Occupational Ergonomics and Human Factors · 2018
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHealth careHuman factors and ergonomicsHealthcare systemEngineering ethicsEngineeringPsychologyMedicinePolitical sciencePoison controlMedical emergency

Abstract

fetched live from OpenAlex

This special issue was driven by the arguably self-evident conclusion drawn by both the Human Factors and Healthcare Systems Engineering communities: People are central to healthcare systems (HCS) and quality patient care.Without skilled, knowledgeable, and well-prepared professional personnel, the healthcare system will not work, regardless of how sophisticated the technology provided is.Ultimately, healthcare is a sociotechnical system (Carayon et al., 2011), and its optimal functioning hinges on the quality of the interaction between the humans and the technological aspects (defined broadly) of the system.Therefore, we assert, the quality of human factors within the system will have a critical effect on the people in the HCS and thus the system's safety and effectiveness.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.403
Teacher spread0.297 · 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