Crisis and the Consolidation of International Accounting Standards: Enron, The IASB, and America
Bibliographic record
Abstract
This paper examines the interplay between leading international and American accounting authorities over the span of a critical four-year period, 2001–2005. Historically, US regulators and private-sector accounting institutions have taken a cautious approach to International Financial Reporting Standards (IFRSs), citing the superior rigor and overall quality of their own Generally Accepted Accounting Principles (GAAP). During the past four years, however, the Securities and Exchange Commission (SEC) and the Financial Accounting Standards Board (FASB) have each become markedly receptive to the International Accounting Standards Board's (IASB) efforts to harmonize accounting standards worldwide based on IFRSs. Why? This paper offers an explanation that highlights the role of the high-profile American corporate scandals (2001–2002) in precipitating a shift in US accounting authorities' views of the optimal form of accounting rules, an issue that has stood in the way of trans-Atlantic accounting standard convergence. Prior to the accounting scandals, the highly-detailed rules that are characteristic of US GAAP were widely seen to be the most effective form of accounting rule. Since 2002, a normative shift has taken place such that the SEC now endorses objectives-oriented rules that are conceptually aligned with the principles-based standards promulgated by the IASB. The analysis is framed by insights from contemporary International Relations theory which emphasize the influence of scope conditions on patterns of governance.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".