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Record W3205924653 · doi:10.38116/rtm26presentation

Presentation: Covid-19 crisis, public policy responses and socioeconomic development: an introduction

2022· article· es· W3205924653 on OpenAlexaff
Cláudio Roberto Amitrano, Marc Lavoie, Pedro Silva Barros

Bibliographic record

Venuenot available
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Presentation (obstetrics)Socioeconomic status2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceEconomic growthEnvironmental healthMedicineEconomicsVirology

Abstract

fetched live from OpenAlex

El texto aborda diversas dimensiones de la crisis de la Covid-19 y sus consecuencias económicas, políticas y sociales en todo el mundo. Inicialmente, se destaca la magnitud del impacto económico de la pandemia, con énfasis en las políticas monetarias y fiscales adoptadas por los países para enfrentar los desafíos a corto y largo plazo. También se discute la influencia de la crisis en la oferta y demanda, así como sus efectos sobre el desempleo, la pobreza y la desigualdad de ingresos. Además, se abordan los impactos en la productividad y las cadenas de producción, destacando sectores como el turismo y el comercio minorista. El texto también explora cuestiones geopolíticas, como la integración regional en América del Sur, y políticas, como el enfoque del gobierno de Estados Unidos en relación con la pandemia. Por último, se examinan temas como la inflación, las políticas de recuperación económica y la regulación financiera. En resumen, el texto proporciona un análisis exhaustivo de las ramificaciones de la crisis de la Covid-19 en diversos aspectos de la sociedad global.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.076
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0760.011

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 head0.069
GPT teacher head0.327
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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