Fair-Value Accounting’s Role in the Global Financial Crisis?: Lessons for the Future
Bibliographic record
Abstract
This paper debates how fair-value accounting (FVA) that were deeply affected by the global financial crisis. Theglobal financial crisis started in advanced economies spreading to emerging markets and low-income countries.Thus, it has been affected in the middle of 2007 and into 2009, which have examined the role of FVA in thefinancial crisis. This paper is used the value-relevance of fair-value reported under FAS 157 that estimates assetsand liabilities in terms of a simple theoretical and empirical analysis literature framework. This empirical studyproposed is a global crisis that not a normal cyclical crisis of capitalism. Also, it requires a change in themanagement policy to be tackled with new regulatory frameworks for financial institutions in order to stimulateeconomic activities. In other words, FVA may have amplified the crisis. Future research is needed to meetup-to-date information regarding the nature of capital markets and financial institutions. This requires a newtheory of economics; for instance, a change from equilibrium theory to reflexivity theory which requires achange in the underlying model of the economic activity framework. Therefore, this study has concluded a newtheory of the change of equilibrium to reflexivity that led to develop the model in the framework of the economicactivity.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".