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 | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| 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".