"GRI PÅ STEROIDER" : Hur en större revisionsbyrå formar och anpassar sig tillEU:s nya direktiv för hållbarhetsrapportering (CSRD)
Bibliographic record
Abstract
The new sustainability directive Corporate Sustainability Reporting Directive [CSRD] isdescribed as the biggest thing that has happened since International Financial ReportingStandards [IFRS] was implemented in the reporting world. A watered-down Non-FinancialReporting Directive [NFRD] will be given new strength through CSRD, which entails higherand stricter requirements for reporting companies to report sustainability information to, amongother things, improve comparability and credibility, and as a step on the way to equatingsustainability reporting with financial reporting. A common way of explaining CSRD at theagency is "GRI on steroids" as a synonym for the higher and more comprehensive requirementsof the directive.This study has been carried out as a case study and aims to create an understanding of auditfirms' perceptions regarding the new sustainability directive CSRD and how they prepare forimplementation. But also, how audit firms are involved in the interpretation and design of thedirective. More precisely, the study has been carried out as a case study of the audit firm KPMG.The purpose of the study has been achieved by first carrying out text analysis which consistedof, among other things, EU documents regarding CSRD, web pages and newspaper interviews.In addition to text analysis, an observation was also carried out which consisted of a webinarfrom European Accounting Association [EAA]. Finally, six interviews were conducted withsustainability experts from KPMG who have extensive knowledge in sustainable business andwho work proactively in the field. Institutional theory has been combined with the threedifferent methods to be able to produce analyses regarding agencies' perceptions about thedirective.In conclusion, the study demonstrates the impact of institutional pressures where there arepressures from different market players pulling in different directions. The institutionalpressures, which are exerted by for example the reporting companies, their stakeholders, andaudit firms, reflect the different players’ interests. Because of these pressures, KPMG needs toadapt its operations to the new directive in order to remain competitive on the market. KPMGis also involved in shaping what the final draft of the directive and the new standards will be,as they are part of the Förenade Auktoriserade Revisorerna [FAR] and the European FinancialReporting Advisory Group [EFRAG] that work to develop and interpret the directive. Becauseof this and the size of the firm, KPMG is able to exert pressure on the standard setters to shapethe final draft of the CSRD in accordance with KPMG’s interests.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.014 |
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".