Bibliographic record
Abstract
Many contemporary organizations claim to be moving towards forms of increased inclusion and transparency in the strategy formulation and communication processes. In particular, openness of strategy-making is a characteristic typically associated with pluralistic settings and public and non-profit organizations. This openness raises however the question of how organizations can enable wide participation while keeping a coherent strategic direction. This paper aims then to shed light on how strategizing takes place in professional, pluralistic contexts, supposedly characterized by open participation in strategy-making. Drawing on a case study of an Italian public hospital that introduced a new participatory planning system, it focuses in particular on how professionals participated in strategy work and the tools they drew on to do so. It explores how professionals strategizing was depicted by the organizational discourse, what professionals actually did, how the adoption of a participatory planning system was taken up and what it enabled in terms of strategy work. The study shows how professionals empowerment is likely to be subject to managerial endorsement. Because of this partial nature, we can consider professionals to be quasi-strategists. It also shows that the simultaneous opening up and holding together of strategy may be accomplished through the boundary spanning activities of planning officers and the channelling and organizing roles of formal planning tools. These findings may increase our understanding of how distributed strategizing occurs in professional settings, offering in turn insight into the processes and the conditions whereby open strategy may play out in organizations 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".