What's the Problem ? Competing Diagnosis and Shifting Coalitions in the Reform of International Accounting Standards
Bibliographic record
Abstract
It does not happen very often that a technical matter such as accounting makes \nit into the final declaration of a G20 summit, agreed by the heads of government of the world’s leading nations. Nevertheless, this happened on November \n15, 2008, two months after the bankruptcy of Lehman Brothers terrified capital \nmarkets and roughly eighteen months after the first signs of the financial crisis \nhad become tangible and started to impact the balance sheets of most banks \nworldwide. After holding their initial meeting as a Group of Twenty in Washington to deliberate about the means to cure the most severe financial crisis since \nthe interwar period, the leaders of the G20 called on their finance ministers to \nformulate recommendations in areas such as “Mitigating against pro-cyclicality \nin regulatory policy” and “Reviewing and aligning global accounting standards, \nparticularly for complex securities in times of stress” (G20 2008). Ever since, \nmeasures to reform international accounting standards – namely, those produced by the International Accounting Standards Board (IASB) – have been \non the working agenda of G20 meetings, even if they have moved from front \nto backstage and are increasingly repeated in terms of the same phrases (see \nthe Declarations of the London, Pittsburgh, Toronto, Seoul, and Paris summits \n(www.g20.org/pub_communiques.aspx).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.096 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.026 | 0.052 |
| Scholarly communication | 0.044 | 0.055 |
| Open science | 0.006 | 0.034 |
| Research integrity | 0.020 | 0.048 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".