Middle Managers, Strategic Sensemaking, and Discursive Competence
Bibliographic record
Abstract
abstract This paper seeks to better understand the way middle managers contribute strategically to the development of an organization by examining how they enact the strategic roles allocated to them, with particular reference to strategic change. Through vignettes drawn from the authors' current research, a framework is developed that shows two situated, but interlinked, discursive activities, ‘performing the conversation’ and ‘setting the scene’, to be critical to the accomplishment of middle manager sensemaking. Language use is key, but needs to be combined with an ability to devise a setting in which to perform the language. The paper shows how middle managers knowledgeably enact these two sets of discursive activities by drawing on contextually relevant verbal, symbolic, and sociocultural systems, to allow them to draw people from different organizational levels into the change as they go about their day‐to‐day work.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".