<i>The Evolution of Management Thought</i>: reflections on narrative structure
Bibliographic record
Abstract
Purpose This paper aims to problematize the dominant narrative forms of disciplinary histories of management thought. Specifically, the authors explore the narrative mode of emplotment used in Wren’s (and later Wren and Bedeian’s) 50-year encyclical on the history of management thought, namely, The Evolution of Management Thought (EMT). Design/methodology/approach The authors propose that management histories operate as powerful narratives that shape our understanding of management thought and, consequently, our disciplinary futures. This paper explores the textual narrative of EMT. Additional data are drawn from other scholars’ observations of this text. This paper is positioned in the debates of management history. Findings While acknowledging the wealth of historical facts in EMT, the authors argue that the umbrella narrative orders events of the past in such a manner that the historical knowledge follows a form of Darwinian evolutionism. Thus, the narrative leads to problematic representations suffering from progressivism, presentism and universalism. Research limitations/implications Disciplinary scholars in management and organization studies need to carefully reflect on how we construct our representations of the past and histories. This will allow us to better craft transparent and reflexive histories. Originality/value To the best of the authors’ knowledge, this paper is the first to propose a remedy, albeit a partial remedy, which we believe is needed to avoid adverse epistemological consequences associated with the use of problematic narratives in management and organizational histories.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.054 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".