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Record W2539013935

Ventajas de los convenios de doble imposición tributaria en la contribución del desarrollo del país.

2011· dissertation· es· W2539013935 on OpenAlexaboutno aff
Romero Velásquez, Kelina Vannesa

Bibliographic record

VenueUniversidad Nacional de Trujillo · 2011
Typedissertation
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsTax evasionLatin AmericansInvestment (military)Welfare economicsForeign direct investmentEconomyDouble taxationPolitical scienceGeographyInternational economicsBusinessEconomicsFinancePublic economicsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

The research developed aims to analyze the advantages it provides to the economy the signing of agreements to avoid double taxation, for which is to review the double taxation agreements that Peru has signed with countries such as Chile, Canada and Brazil, which consist in an article for the elimination of double taxation, in the case of double taxation agreements with Chile and Canada can be found in Article 23 and Article 22 with Brazil, which is a tool to address international tax evasion. As result has found that foreign investment in Peru in the year 2010 was 20 781 million dollars has like the largest investors Spain, United Kingdom and United States with 21.2%, 21.04% and 15.24% respectively, grow the way 7285 million to 20781 million dollars 1997 to 2010, and according to the table of macroeconomic indicators the gross investment so far of 2010 obtained 25.1% of PIB, being the private investment most important with a share 19.2%, was revised agreements with Canada, Brazil and Chile, doing know how to avoid double taxation. We used the method of documentary analysis, analysis of investment behavior at the level of Latin America and the country that matches the increase in global agreements. Finally, this research to give known the advantages over double taxation agreements for the contribution of economic development of country.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.219
Teacher spread0.208 · 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.

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
Published2011
Admission routes1
Has abstractyes

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