Strategy as Simulacra? A Radical Reflexive Look at the Discipline and Practice of Strategy*
Bibliographic record
Abstract
ABSTRACT Over the past three decades strategic management has become a crucial aspect of business education and practice. At the core of strategic management – linking technique to worldview – is modelling (e.g. value chain, SWOT analysis) whereby the complex elements of strategic thinking are simplified. This accounts in large part for the apparent popularity of strategic management as complex interrelationships are pursued through relatively simple models. Yet has the field of strategic management realized the third order of simulacra? Is strategic management a model of simulation whereby reality has been replaced by hyperreality? A review of the extant literature on strategy explores the study and practice of strategy as a discourse, engulfed by its own truth effects. An examination of the concepts of reflexivity demonstrates the value of a postmodern radical reflexive account through the application of Baudrillard's (1983 , 1988 , 1991 , 1994 ) simulation and simulacra. It is through the development of a radical reflexive discourse of strategy as simulacra, this paper critically examines the study and practice of strategy and the lessons we can take from this perspective.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.056 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".