The Role and Impact of International Financial Reporting Standards on Cross-Border Financing for a Systemically Important Bank from Macroeconomic Perspectives—Technical Review Research Study
Bibliographic record
Abstract
The author of the study note that the extensiveness of a country’s international accounting disclosure requirements is a good for the overall disclosure extensiveness of the exchange in that foreign country, which, in turn, is bigly correlated with the cost of listing such as United States, Canada, United Kingdom, The Netherlands, France, Japan, and Germany. The United States and the national over-the-counter market have enjoyed significant growth in foreign listing. In absolute terms, the U.S. numbers are even more impressive. As of December 2019, the 1,420 foreign companies whose shares are traded in the United States reparent the largest amount of foreign listings of any major stock exchange in the world., which reflects, at least in part, recognition by multinational entities that the U.S. securities market represents the most efficient market in the world, thus translating into a lower cost of capital for issuer of securities. This technical research review article may support both the public trade companies and policymakers around the World.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".