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Record W3140502103 · doi:10.1017/bca.2021.5

Economic Activity and the Value of Medical Innovation during a Pandemic

2021· article· en· W3140502103 on OpenAlexaboutno aff
Casey B. Mulligan

Bibliographic record

VenueJournal of Benefit-Cost Analysis · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsnot available
Fundersnot available
KeywordsShutdownNonmarket forcesQuarter (Canadian coin)Activity-based costingValue (mathematics)FellPandemicProduction (economics)EconomicsCoronavirus disease 2019 (COVID-19)BusinessMarket economyFactor marketGeographyEngineeringMacroeconomicsAccounting

Abstract

fetched live from OpenAlex

Abstract The “shutdown” economy of April 2020 is compared to a normally functioning economy both in terms of market and nonmarket activities. Three novel methods and data indicate that a full shutdown of “nonessential” activities puts market production about 25 % below normal in the short run. At an annual rate, a full shutdown costs $9 trillion, or about $18,000 per household per quarter. Employment already fell 24 million by early April 2020. These costs indicate, among other things, the value of innovation in both health and general business sectors that can accelerate the time when, and the degree to which, normal activity resumes.

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)0.011
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.316
GPT teacher head0.519
Teacher spread0.203 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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