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Record W2615314383 · doi:10.1177/2327857917061051

Who is Drinking Our Kool-Aid? Hear Clinicians’ Perspective of their Human Factors Practitioner

2017· article· en· W2615314383 on OpenAlex
Adjhaporn Khunlertkit, A. Joy Rivera, Shanqing Yin, Laurie Wolf, Dean Karavite, Catherine Dulude, Susan Harkness Regli

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

VenueProceedings of the International Symposium on Human Factors and Ergonomics in Health Care · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsPerspective (graphical)PerceptionHealth careMedicineEXPOSEMedical educationPublic relationsPsychologyNursingComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Human factors (HF) has multiple domains that integrate various disciplines; and its principles and methods can be diversely applied within an organization. Healthcare organizations have started to deploy HF Practitioner (HFP) to assist in enhancing patient safety. However, the path for HFP integration into a hospital is still immature, clinical staff may be unclear of how to effectively collaborate with their HFP, and what benefits could HFP provide. This panel brings in 5 panelists from different organizations, who will share their experience in collaborating with their clinical advocate. Most importantly, audiences will hear their clinician advocates’ perceptions of the collaborations and benefits that their HFP has delivered, which encouraged them to drink our HFP ‘Kool-Aid.’

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.273
GPT teacher head0.549
Teacher spread0.275 · 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