La demanda global y los ingresos tributarios en el periodo post pandemia 2020 - 2021
Bibliographic record
Abstract
The different economic postulates maintain that economic growth must necessarily lead to an increase in tax collection, unless the levels of informality are very high. The current doctoral thesis carries out an investigation to determine the relationship between global demand and tax income in the post-pandemic period 2020 - 2021. For this purpose, this Quantitative type, Correlational level and non-experimental design. The research concludes that Global Demand is directly related to Tax Revenue in the post-pandemic period 2020 - 2021, demonstrated with the Correlation Coefficient r = 0.861502676; and the Coefficient of Determination R2 = 0.752186860. Likewise, it has been verified that the Internal Demand determines the behavior of the Global Demand, having obtained a Correlation Coefficient r = 0.998999691; and the Coefficient of Determination R2 = 0.998000382. On the other hand, the value of Internal Demand is determined by the behavior of Private Final Consumption Expenditure, a concept that reached the amount of S/. 677,602.00 million, equal to 63.76% of the total. The analysis of Tax Revenues shows that these had a growing evolution in general terms, with the exception of the II quarter of 2020 where there was a contraction of -23.68%, because of the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".