Planeamiento tributario y la rentabilidad de la empresa CLÍNICA SANTA ANA, trujillo 2017
Bibliographic record
Abstract
The main objective of this research work is to determine how tax planning affects the \nprofitability of the company Clinic Santa Ana, for which the Chi-square test was applied to \ndetermine if there are changes between the profitability ratios when performing the \ncomparison corresponding to the first quarter of 2017 and after 2018, as a consequence of \nhaving applied tax planning, finding a value of p = 0.0098 less than 0.05, which allows us \nto affirm that there is a significant difference. \nThe design of the research is explanatory ex post - facto, it was used to verify the \nhypothesis, as well as the relationship between the tax planning and profitability variables, \nand under what circumstances the study situation developed before and after having \napplied the tax planning. In this way, in order to carry out this research study, the \neconomic and financial information of the company shown in the Balance Sheet and the \nIncome Statement for the first quarter of 2017 and after the current year has been taken \ninto account. The results obtained when implementing an adequate Tax Planning in the \ncompany are; it allows to optimize the material, financial resources and the human talent \nthat it possesses. It allows not to incur in infractions and therefore the non-payment of fines \nand late fees. \nIn order to carry out this research, data collection techniques were used, such as the \nquestionnaire to know the tax situation of the company Clinic Santa Ana, together with a \ndocumentary analysis, through the collection of information. \nFinally, when applying the tax planning to the company Clínica Santa Ana, it was shown \nthat it is ready to face an audit. Also minimize the tax burden, taking into account that \nplanning is a structured tool according to the regulations in force.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".