ESG Outcasts: Study of the ESG Performance of Sin Stocks
Bibliographic record
Abstract
Certain economic actors are considered by many as involved in or associated with an activity that is considered unethical or immoral, such as the producers of tobacco, alcohol and firearms (often referred to as sin stocks). In an environment in which stakeholders are increasingly interested in sustainable development and corporate social responsibility, it is important to understand how firms respond to these issues which divide public opinion. Our study compares the environmental, social and governance (ESG) performance for a targeted sample of 79 sin stocks and a control group of comparable firms. We observe that sin stocks have a lower overall ESG performance as well as for each of the three ESG pillars, and that this difference is more significant in relation to governance and some key social and environmental issues for which sin stocks could have compensated risk exposure with responsible management practices. In other words, our results demonstrate that sin stocks are exposed to more severe ESG issues and consistently lack the necessary practices to mitigate these issues. Our study provides relevant insights into the informativeness of ESG scores to distinguish firms (and sectors) investing in management practices that offset ESG risk exposure.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".