Environmental disclosures and <scp>ESG</scp> fund ownership
Bibliographic record
Abstract
Abstract In this study, we examine whether environmental, social, and governance (ESG) funds' investment decisions are sensitive to the existence and extent of firms' voluntary environmental disclosures. We create our measures of voluntary environmental disclosure using bigrams extracted from the Global Reporting Initiative standards. We provide robust evidence that voluntary environmental disclosure in conference calls is associated with greater ESG fund ownership in the subsequent period, incremental to firms' ESG ratings. We also provide evidence that fund managers' reliance on environmental disclosure is concentrated in water, waste, emissions, and compliance disclosures. ESG fund ownership increases with environmental disclosure that is more positive and specific. Our primary finding persists both when we rely on the sustainability report as an alternative proxy for environmental disclosure and when we use fund‐level tests. Overall, our evidence is consistent with ESG funds relying on firms' disclosures when making investing decisions and inconsistent with recent regulatory concerns that ESG fund managers are not following through on their stated investing strategies.
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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 | 0.005 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".