Business Versus Ethics? Thoughts on the Future of Business Ethics
Bibliographic record
Abstract
To commemorate 40 years since the founding of the Journal of Business Ethics, the editors in chief of the journal have invited the editors to provide commentaries on the future of business ethics. This essay comprises a selection of commentaries aimed at creating dialogue around the theme Business versus Ethics? (inspired by the title of the commentary by Jeffrey Harrison). The authors of these commentaries seek to transcend the age-old separation fallacy (Freeman in Bus Ethics Q 4(4):409–421, 1994) that juxtaposes business and ethics/society, posing a forced choice or trade off. Providing a contemporary take on the classical question “if it’s legal is it ethical?”, David Hess explores the role of the law in promoting or hindering stakeholder-oriented purpose and governance structure. Jeffrey Harrison encourages scholars to move beyond the presupposition that businesses are either strategic or ethical and explore important questions at the intersection of strategy and ethics. The proposition that business models might be inherently ethical or inherently unethical in their design is developed by Sheila Killian, who examines business systems, their morality, and who they serve. However, the conundrum that entrepreneurs are either lauded for their self-belief and risk-taking, or loathed for their self-belief and risk-taking, is discussed by M. Tina Dacin and Julia Roloff using the metaphor of taboos and totems. These commentaries seek to explore positions that advocate multiplicity and tensions in which business ethics is not either/or but both.
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 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 | 0.023 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.056 |
| Scholarly communication | 0.023 | 0.025 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.024 | 0.026 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".