Análisis a las observaciones realizadas por la Superintendencia de Valores y Seguros a los primeros estados financieros confeccionados bajo IFRS en Chile
Bibliographic record
Abstract
In Chile, the first financial statements done under International Financial Reporting Standards \n(IFRS) reveal the results of the first quarter of 2009. During that year a group of companies controlled \nby the Superintendent of Securities and Insurance (SVS for its acronym in Spanish) were required \nto provide financial statements under the new accounting standard. This report aims to determine \nwhat types of observations the SVS had about the information provided in the financial statements \nunder IFRS provided for the year 2009, as well as to determine whether there was a change in the \nextent of information provided by the companies observed. Based on a representative sample of 45 \ncompanies, 73.33% were observed by the SVS. Notifications are classified into the following topics: \na) Failure to comply with reporting requirements detailed in the information models developed by \nthe SVS, b) Omissions and / or errors in the explanations of accounting policies carried out in the \npreparation and presentation of the financial statements, c) Omissions and / or errors in the detail \nprovided in the explanatory notes of the financial statements d) Voluntary resending by companies of \ntheir financial statements with omissions and / or errors corrected, and e) Inconsistency between the \nfinancial information provided in the PDF format and the XBRL file. The results show that there is a \nstatistically significant increase in the amount of information provided by the companies reported in \n2009. Additionally a qualitative analysis was developed for the five types of observations identified in \nthis study. In virtue of the upcoming implementations of IFRS, both locally (unregulated companies) \nand at the South American level, this study provides significant evidence of the relevant factors \ninvolved in normative compliance and reporting transparency when applying IFRS for the first time.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".