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FISCAL POLICY OF THE RUSSIAN FEDERATION DURING THE PERIOD OF QUARANTINE RESTRICTIONS OF 2020

2021· article· en· W4245201025 on OpenAlexaboutno aff
Mikhail Gordienko

Bibliographic record

VenueEKONOMIKA I UPRAVLENIE PROBLEMY RESHENIYA · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationQuarantineQuarter (Canadian coin)Economic policyFiscal policyPeriod (music)Federal budgetTax policyEconomicsFiscal yearBusinessPolitical sciencePublic economicsMacroeconomicsFinanceTax reformGeographyMedicine

Abstract

fetched live from OpenAlex

The article is devoted to the consideration of the issues of the fiscal policy of the Russian Federation in the field of income in the acute quarantine period of 2020 and its preliminary results. According to the chro-nology, first, a review of the results and plans of the pre-quarantine year 2019 is carried out, with which the budgetary and tax system of Russia entered a series of difficult-to-predict events in 2020. The indicators of income at the federal and regional levels are analyzed, as well as the stabilization measures of the budgetary and tax policy under the results of the first quarter, 1st half of the year and available data for 2020.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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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