Bibliographic record
Abstract
An environmental accident at a Placer Dome mine in the Philippines provides the context for this event study. This accident triggered a contagion effect across the Canadian mining industry. The decline in equity prices was moderated by environmental information disclosed prior to the accident. There is evidence to support the interpretation by Blacconiere and Patten –in their 1994 study of the Union Carbide accident – that investors interpret environmental disclosure as a signal of the extent to which the company is managing environmental risks and costs. In this current research, however, the modifying effect of disclosure is limited to information on high- level commitment to environmental stewardship. This paper draws on legitimacy theory to explain the image companies wish to project to their external audience, and signal theory for insight into how managers decide what information to disclose. The paper extends prior research into signal theory by examining the association of the disclosed signal with actual environmental performance. The correlation of disclosure with the volume of National Pollutant Release Inventory emissions is negative, suggesting that companies with a high-level commitment are better environmental performers. The findings of this study are consistent with prior research that examines factors contributing to disclosure credibility. While this study supports the conclusion that investors interpret disclosure to be a signal, it does not
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.653 | 0.272 |
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".