A Review of Corporate Social Responsibility and Reputational Costs in the Tax Avoidance Literature*
Bibliographic record
Abstract
ABSTRACT In recent years, academic researchers, policymakers, and the public have increasingly focused on the tax avoidance behavior of corporations. At the same time, firms are increasingly pressured to incorporate corporate social responsibility (CSR) into their decision making, leading to heightened academic interest in CSR. Given that opponents of corporate tax avoidance often argue that avoiding tax is socially irresponsible, we review the growing literature surrounding this issue. We begin with a theoretical review of how corporate tax avoidance fits into the CSR framework. We then review the empirical evidence on the interrelationship between CSR and firm reputation in the tax avoidance literature. We frame our review around three questions: (i) Do firms view tax avoidance as a CSR issue? (ii) Do stakeholders view tax avoidance as socially irresponsible, leading to reputational costs of tax avoidance? And (iii) Do firms change their tax avoidance behavior due to fear of these reputational consequences? Throughout our review, we provide discussions on the state of the current literature and offer suggestions for future research opportunities.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".