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Record W4391889664 · doi:10.1098/rsos.231102

Imagination and idealism after the COVID-19 pandemic: the science of healthy ageing

2024· article· en· W4391889664 on OpenAlexaff
Colin Farrelly

Bibliographic record

VenueRoyal Society Open Science · 2024
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsQueen's University
Fundersnot available
KeywordsIdealismPandemicCuriosityCoronavirus disease 2019 (COVID-19)Medical sciencePromotion (chess)AffectionPsychologyMedicineSociologyEnvironmental ethicsPolitical scienceEpistemologySocial psychologyPhilosophyLawMedical educationPathologyDiseasePolitics

Abstract

fetched live from OpenAlex

On 5 May 2023, the World Health Organization declared that COVID-19 no longer constituted a public health emergency of international concern. Medical science must now consider how it ought to recalibrate its imagination and idealism in a post-COVID-19 pandemic world. The fact that advanced age was the largest risk factor for COVID-19 mortality and serious illness, as well as for the most prevalent chronic diseases, reveals the urgency and significance of shifting the focus from mitigating each specific pathology risk, one at a time, to targeting biological ageing itself. In his 1910 JAMA Address entitled ‘Imagination and Idealism in the Medical Sciences', Christian Herter made an important distinction between two ways imagination and idealism can be invoked in the medical sciences: (i) humanitarian medicine, which emphasizes the obvious and direct paths of ameliorating human suffering; and (ii) a curiosity-oriented approach which explores pure science and the experimental laboratory. The latter examines the indirect ways of winning, in Herter's words, ‘the citadel’ of health promotion. Herter's reflections on these two contrasting approaches to medicine have significance for both the COVID-19 pandemic and the aspiration to promote the ideal of healthy ageing in the post-COVID-19 pandemic era.

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 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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
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 head0.038
GPT teacher head0.396
Teacher spread0.358 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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