Economic and Political Objections to “Moral Capitalism”
Bibliographic record
Abstract
Abstract As corporations increasingly embrace ethical commitments and prioritize corporate social responsibility (CSR), commentators have begun to speak of a shift toward “moral capitalism.” This shift has revived debates about the compatibility of CSR with economic efficiency and the role of markets in promoting social change. We find the economic concern misplaced: moral capitalism efficiently responds to a growing demand for CSR from all stakeholders, including shareholders. Yet the same market mechanisms that make modern CSR profitable raise political objections worth considering. Major shareholders can now leverage their disproportionate economic power to use corporations as vehicles for forcing unilateral resolutions of societal issues, bypassing and undermining formal democratic processes. Beyond this, there is a broader risk to social cohesion: when markets become arenas for adjudicating rather than sidestepping moral and political disagreements, they reinforce exchanges among “friends” (those with shared preferences) while deepening divisions with “foes.” This may import polarization into market life, with spillover effects on society at large. Taken together, these concerns raise the question of whether moral capitalism may threaten the very democratic moral sensibility it claims to uphold.
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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 | 0.022 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.058 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".