Does Alignment with the IIRF Influence Capital Markets? Evidence from South Africa and the UK
Bibliographic record
Abstract
This study examines whether integrated reports that are more closely aligned with the International Integrated Reporting Framework (IIRF) are differently associated with firm value compared to those less aligned. Using panel estimated generalised least squares and other robust estimations, the analysis covers the Top 100 firms listed on South Africa’s Johannesburg Stock Exchange and the United Kingdom’s London Stock Exchange from 2011 to 2018. South Africa presents a mandatory integrated reporting (IR) setting, while the UK adopts a voluntary approach, offering a natural comparative context. An IR quality index was constructed to measure the degree of alignment with the IIRF, and market value of equity and Tobin’s Q are used as proxies for firm value. The results show no evidence of capital market differentiation in South Africa between more and less IIRF-aligned reports. In contrast, UK capital markets may differentiate, with less-aligned reports showing a significant negative association with firm value. These findings suggest that low-quality integrated reports may undermine firm value in voluntary IR settings.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".