Do financial penalties for environmental violations facilitate improvements in corporate environmental performance? An empirical investigation
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
Abstract Environmental regulations play an essential role in managing firm behavior and providing a reference point for the minimum standards of corporate environmental performance, yet certain firms fail to ensure their environmental performance meets these standards. This research focuses on public firms that the US government has penalized for violating environmental regulations and investigates whether these firms subsequently improved their environmental performance. Surprisingly, neither the receipt of a penalty for an environmental violation nor the imposition of a greater penalty was associated with improvements in environmental performance. Instead, a penalty for environmental violation predicted further, albeit mild, deterioration in environmental performance. While the existing literature has established that financial penalties deter most firms from committing environmental violations, this research contributes to this literature by revealing that these penalties fail to motivate firms that have violated environmental regulations to improve their environmental performance.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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