Regulatory Response to Tackle the Anticipated Repercussions of Covid-19
Bibliographic record
Abstract
Covid 19 pandemic has disrupted work and working environment across the globe. In most economies the industry and services sector has borne the brunt of lockdown and shutdown. Thankfully, the banking sector and capital markets have been functioning without disruption. In order to ensure business continuity, various regulations have been relaxed and the flow of information to the markets is expected to be delayed. The same will be further complicated by the fact that the last quarter results of financial year 2019-20 and the at least first quarter results of the year 2020-21 is expected to be affected by the pandemic and hence make it difficult for analysts to compare, evaluate and predict. Similarly accountants are expected to face various problems in application of the accounting standards while finalizing the accounts and auditors while providing their audit reports.This article attempts to provide an overview of some of the regulatory responses and ways to tackle the anticipated challenges to disclosures and other accounting related issues.
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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 | 0.059 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.022 | 0.022 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".