The role of existentialism in ethical business decision‐making
Bibliographic record
Abstract
This paper presents an integrated model of ethical decision‐making in business that incorporates teleological, deontological and existential theory. Existentialism has been curiously overlooked by many scholars in the field despite the fact that it is so fundamentally a theory of choice. We argue that it is possible to seek good organisational ends (teleology), through the use of right means (deontology), and enable the decision‐maker to do so authentically (existentialism). More specifically, we provide a framework that will enable the decision‐maker to integrate the various ethical schools of thought available to them and to apply this framework in the ethical decision‐making process. The model presented makes explicit the existential position of choice and takes into account other contextual moderating factors. Negative Option Marketing is used as a running application to illustrate the role of existentialism in the decision‐making process.
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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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.051 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| 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".