The multiverse of non-financial reporting regulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although non-financial reporting (NFR) has been extensively explored in the accounting literature, most previous studies have focused on relevant issues in contexts where firms report their impact on society and the natural environment voluntarily. Despite the important role previous studies on voluntary NFR play in our understanding over of its role, processes and consequences, extant literature has provided limited evidence on (i) how NFR regulation affects (if at all) corporate reporting, (ii) whether such regulated reporting affects the users of corporate reports and, (iii) whether mandatory NFR has any “real effects” on how firms affect society and natural environment. This special issue attempts to enrich our understanding of the impact of NFR regulation with reference to the studies accepted for the special issue. In addition, this paper discusses key aspects of NFR regulation, provides an overview of the papers included in the special issue and proposes further axes of research in light of the continuing reforms in the NFR regulatory space; which we foresee to lead to a “multiverse” of NFR regulatory models and approaches.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it