Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the current gap between the subjects of business ethics and pre‐1960 management theory. Design/methodology/approach In an attempt to achieve the objective of the paper, the business ethics content of three leading management theorists during the first half of the 1900s is examined: Frederick Taylor; Chester Barnard; and Peter Drucker. Findings The paper concludes that there are significant business ethics content as well as ethical implications in the writings of each of the three management theorists. Research limitations/implications The analysis focused on only three, albeit significant, management theorists. A more complete discussion would have included other important management theorists as well. Practical implications The analysis suggests that management theory should not be taught without discussing both the business ethics implications and the business ethics content inherent in the theory. In addition, failure on the part of business ethics academics to understand early management theory, the ethical ramifications of such theory, and the business ethics issues explicitly discussed by leading management theorists, may lead to teaching and research in a subject without a proper theoretical foundation. Originality/value The paper attempts to address a gap in management literature by demonstrating some of the linkages between business ethics and business management thought, and thereby be of value to management theorists as well as business ethicists in their teaching and research efforts.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.028 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| 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".