Impacto en la adopción de las NIIF en Colombia
Bibliographic record
Abstract
Convergence is the participation of two or more events that influence the same point of view, in this case of having a universal language leads to the implementation of International Financial Reporting Standards (IFRS), also known by its acronym in English (IFRS) International Financial Reporting Standard, which are largely influenced by different agreements or free trade agreements where there is greater access to financial information at the global level. For this reason, it is essential to standardize information and accounting language for the preparation of the different reports and real interpretations of business situations, to improve their financial function, improvements in accounting policies, and to be efficient with the presentation of financial statements. in a unified and transparent way. \nColombia currently has fifteen free trade agreements which are in different countries such as Mexico, Chile, the United States, Canada, Cuba, the European Union, Korea and other commercial alliances in the country, in order to strengthen the economic integration at the regional level, opening of markets for goods and services, programming and liberalization of tariffs, and trade financing; Colombian companies perform the standardization of accounting information to unify the concepts, allowing investors to make decisions and open new business alliances. \nThe adoption of IFRS in Colombia has been marked by different challenges at the structural, and perhaps operational, level. It is important to warn entrepreneurs, public accountants and managers about the real challenges that organizations must face with the adoption and implementation of International Financial Reporting Standards and to offer a tentative interpretation of the impacts that this convergence generates on Colombian companies
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".