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Record W3135949566 · doi:10.17976/jpps/2021.02.02

Covid-19 Pandemic and the World Order

2021· article· en· W3135949566 on OpenAlexaff
Elena Chebankova, Petr Dutkiewicz

Bibliographic record

VenueПолис Политические исследования · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)CapitalismPolitical economyElitePolitical scienceOrder (exchange)IdeologyWorld orderPoliticsDevelopment economicsPower (physics)SociologyEconomicsLawMedicine

Abstract

fetched live from OpenAlex

This paper examines the origins, nature, and potential outcomes of the global crisis induced by the Covid-19 pandemic. The authors argue that the crisis has been animated by the two most important groups of factors that have been simmering in the world‘s economic and political system during the past six decades and have been accelerated by the pandemic. First, the dynamic of the Covid-19 crisis illuminated the existing challenges of the contemporary capitalist system, which is generally legitimated via the instruments of moral panic and media manipulation. Each consecutive crisis of capitalism ends with the redistribution of power resources to some groups of participants. Second, the Covid-19 crisis has been taking place within the conditions of a systemic and ideological struggle between two global elite factions that harbour drastically different approaches to the changing world order and have different politico-economic goals and intentions. The authors will argue that the crisis will not change the world drastically, yet it will amplify these ongoing tensions, illuminate them to many general observers, and deepen the already-existing systemic instability.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0040.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.126
GPT teacher head0.470
Teacher spread0.344 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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