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International Experience of Income Taxation of Individuals and Directions of Improvement of the Tax System of the Russian Federation

2024· article· en· W4393280515 on OpenAlex
Phuong Thinh Chan, Olga V. Staroverova

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScientific Research and Development Economics of the Firm · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Issues
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationInternational taxationBusinessDouble taxationIncome taxEconomic policyPolitical scienceEconomicsPublic economicsTax reform

Abstract

fetched live from OpenAlex

The article examines the international experience of personal income taxation in developed countries such as the United States of America (USA), the United Kingdom, Japan, China, Australia, Canada, and Germany. The study was conducted using general scientific methods of cognition, including observation, comparison, data collection and analysis, deduction, and induction. The sources of information for the study were regulatory and legislative acts, as well as electronic resources. The main findings include reform of the personal income tax (PIT), aimed at increasing revenues, but not too heavy a tax burden for taxpayers and ensuring fairness, is a matter of concern at present. The study of tax systems in other countries allows us to identify effective approaches to the development and implementation of tax reforms, as well as to avoid mistakes made in other states.

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.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.054
GPT teacher head0.355
Teacher spread0.301 · 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