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Record W3129249118 · doi:10.5539/jpl.v13n4p81

Social and Political Development Strategies: Global Pandemic Challenges (Covid-19)

2020· article· en· W3129249118 on OpenAlexvenueno aff
Karabushenko Paul Leonidovich, Mamychev Alexey Yurievich, Vorontsov Sergey Alekseevich, Kim Alexander Alekseevich

Bibliographic record

VenueJournal of Politics and Law · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSociopolitical Dynamics in Russia
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsElitePoliticsCompetence (human resources)Coronavirus disease 2019 (COVID-19)Political sciencePandemicConsciousnessPolitical economyPublic relationsSociologyDevelopment economicsPsychologySocial psychologyLawMedicineEconomics

Abstract

fetched live from OpenAlex

Even English historian A. Toynbee claimed that each new generation of the “creative minority” (elite) periodically faced challenges of the time, to which it had to seek and give an adequate response. In case of an unsatisfactory answer, this “creative minority” should leave the historical stage, giving way to the more competent elite. The coronavirus crisis experienced by the global community in 2020 has become such a global challenge of our time for many people. And the public can make conclusions about the professional training and level of competence of the ruling elite groups judging from how effectively they cope with this challenge. But even now it can already be stated that the crisis has revealed a number of significant systemic failures in the functioning of political elites - their slow reaction to the event, disunity, clip consciousness and underestimation of the degree of risk, resources and their own capabilities. This article is devoted to the analysis of all these problems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.147
GPT teacher head0.423
Teacher spread0.276 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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