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Record W3193476553 · doi:10.3390/su13179556

ESG Outcasts: Study of the ESG Performance of Sin Stocks

2021· article· en· W3193476553 on OpenAlexaff
Gabriel Paradis, Eduardo Schiehll

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsBusinessCorporate social responsibilityCorporate governanceAccountingControl (management)Sample (material)Social responsibilitySustainable developmentFinancePublic relationsEconomicsEcologyManagementPolitical science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.261
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2021
Admission routes1
Has abstractyes

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