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Record W3048829241 · doi:10.1093/intqhc/mzaa094

Crisis standards of care in a pandemic: navigating the ethical, clinical, psychological and policy-making maelstrom

2020· article· en· W3048829241 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

VenueInternational Journal for Quality in Health Care · 2020
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of TorontoUniversity of Victoria
Fundersnot available
KeywordsPandemicPopulationHealth carePublic relationsResource (disambiguation)Political scienceBusinessPsychologyMedicineNursingCoronavirus disease 2019 (COVID-19)LawEnvironmental health

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has caused clinicians at the frontlines to confront difficult decisions regarding resource allocation, treatment options and ultimately the life-saving measures that must be taken at the point of care. This article addresses the importance of enacting crisis standards of care (CSC) as a policy mechanism to facilitate the shift to population-based medicine. In times of emergencies and crises such as this pandemic, the enactment of CSC enables concrete decisions to be made by governments relating to supply chains, resource allocation and provision of care to maximize societal benefit. This shift from an individual to a population-based societal focus has profound consequences on how clinical decisions are made at the point of care. Failing to enact CSC may have psychological impacts for healthcare providers particularly related to moral distress, through an inability to fully enact individual beliefs (individually focused clinical decisions) which form their moral compass.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
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 integrity0.0000.002
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 head0.283
GPT teacher head0.678
Teacher spread0.395 · 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