The emergence of integrated private reporting
Bibliographic record
Abstract
Purpose – This paper aims to provide evidence to suggest that private social and environmental reporting (i.e. one-on-one meetings between institutional investors and investees on social and environmental issues) is beginning to merge with private financial reporting and that, as a result, integrated private reporting is emerging. Design/methodology/approach – In this paper, 19 FTSE100 companies and 20 UK institutional investors were interviewed to discover trends in private integrated reporting and to gauge whether private reporting is genuinely becoming integrated. The emergence of integrated private reporting through the lens of institutional logics was interpreted. The emergence of integrated private reporting as a merging of two hitherto separate and possibly rival institutional logics was framed. Findings – It was found that specialist socially responsible investment managers are starting to attend private financial reporting meetings, while mainstream fund managers are starting to attend private meetings on environmental, social and governance (ESG) issues. Further, senior company directors are becoming increasingly conversant with ESG issues. Research limitations/implications – The findings were interpreted as two possible scenarios: there is a genuine hybridisation occurring in the UK institutional investment such that integrated private reporting is emerging or the financial logic is absorbing and effectively neutralising the responsible investment logic. Practical implications – These findings provide evidence of emergent integrated private reporting which are useful to both the corporate and institutional investment communities as they plan their engagement meetings. Originality/value – No study has hitherto examined private social and environmental reporting through interview research from the perspective of emergent integrated private reporting. This is the first paper to discuss integrated reporting in the private reporting context.
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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 | 0.016 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".