The Path Towards International Non-financial Reporting Framework
Bibliographic record
Abstract
Purpose/Aim: Over the last quarter of a century, several voluntary frameworks and non-financial reporting standards have been developed by various initiatives and organisations. Especially after the 2008 financial crisis, which deepened into values crises, the need for evaluating social, environmental, and economic consequences and herein for non-financial disclosures accrued. This chapter aims to outline the current state in the ecosystem for non-financial reporting and its projected future developments and suggests further developments in this field. Since financial institutions played a negative role in the crises and will be important in future responsible investing, the authors also addressed some financial institutions’ specific non-financial issues.Method: In search of an answer to our questions about whether existing non-financial reporting pronouncements meet (various) stakeholders’ expectations and whether international pronouncements are needed, we rely on triangulation. We start with the identification of phenomena of non-financial reporting. Description of phenomena is further on supplemented with a literate overview. Based on a review of prior research and study of the current framework’s pros and cons, we present a possible path of further development in non-financial reporting. Making that mixed-methodological approach is used (i.e. deductive and inductive reasoning).Results/Findings: The authors deduce that there has been a substantial increase in demand for non-financial information, social responsibility ratings and other non-financial information services on behalf of preparers, users of such reports and the public. The authors particularly highlight the shortcomings that currently exist and outline the characteristics that future international non-financial reporting frameworks would have to meet with the awareness that such framework or standards will have their advantages and disadvantages. As seen by the authors, the main problem is how to achieve political consensus and then general acceptance by users.Originality/Significance: The International Financial Reporting Standards (IFRS) Foundation has become active in the field of non-financial reporting and started a project to become an internationally recognised standard-setter. However, with many mandatory or voluntary initiatives being started in this field, IFRS Foundation will need to address many challenges and ambiguities to become a leading organisation in non-financial reporting. Therefore, the research question is whether a new board, comparable to the International Accounting Standards Board, with the straightforward task of setting non-financial reporting standards would be needed in the future.
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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 | 0.365 | 0.272 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.010 | 0.046 |
| Scholarly communication | 0.042 | 0.056 |
| Open science | 0.011 | 0.015 |
| Research integrity | 0.012 | 0.019 |
| 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".