Professionals as Strategists? Channelling and Organizing Distributed Strategizing
Bibliographic record
Abstract
Many contemporary organizations claim to be moving towards forms of increased inclusion\nand transparency in the strategy formulation and communication processes. This paper\nexplores how organizations can enable wide participation in strategy making while keeping a\ncoherent strategic direction. In particular, it investigates how strategizing takes place in\nprofessional, pluralistic contexts, supposedly characterized by open participation in strategymaking.\nDrawing on a strategy-as-practice perspective and on a case study of an Italian public\nhospital that introduced a new participatory planning system, it focuses on how professionals\nparticipated in strategy work and the tools they drew on to do so. The study shows how\nprofessionals’ empowerment is likely to be subject to managerial endorsement and how the\nsimultaneous opening up and holding together of strategy may be accomplished through the\nboundary spanning activities of planning officers and the channelling and organizing roles of\nformal planning tools. These findings contribute to an understanding of how distributed\nstrategizing occurs in professional settings and how ‘open strategy’ may play out in\norganizations more generally.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".