Teaching multiple approaches to management to facilitate prosocial and environmental well-being
Bibliographic record
Abstract
Friedman's maxim "The social responsibility of business is to increase its profits" (p. 32) has shaped what managers consider effective management. This Financial Bottom Line approach to management has been challenged by both Positive Organizational Scholarship (POS) and Critical Management Studies (CMS). POS highlights how enhancing prosocial and other nonfinancial considerations can increase profits, consistent with the current dominant Triple Bottom Line approach. In contrast, CMS tends to critique any approach that seeks to maximize profits by creating dysfunctional power symmetries and marginalization. This study introduces a third option, the Social and Ecological Thought approach, which promotes maximizing social and ecological well-being while remaining financially viable. A longitudinal pre-post intervention in a sample of undergraduate management students showed that teaching multiple approaches to management-Financial Bottom Line, Triple Bottom Line, and Social and Ecological Thought-resulted in learners becoming less likely to espouse profit-related goals (e.g. to maximize efficiency, productivity, profitability) and more likely to identify nonfinancial ones (e.g. extra-organizational prosociality and reduction of marginalization) when characterizing effective management. However, the results did not support predictions regarding intra-organizational prosociality and marginalization, or power asymmetries. We discuss implications for pedagogy and the future development of POS and CMS.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".