Embodying and Materializing Strategic Change through Live Presentations
Bibliographic record
Abstract
This paper seeks to develop the idea that researchers using a socio-material lens to examine strategy making should take the body into account. Strategy tools cannot be produced, diffused and appropriated without being embodied. Yet, the body as an animate artefact has not been taken seriously in the strategy-as-practice field. Drawing on an ethnographic study of a strategic change in the healthcare environment, we examine “PowerPoint presentations” of a cultural change initiative to different audiences. The paper shows how through these “PowerPoint presentations,” the main promoter of the change (1) materializes the strategic change by embodying different subject positions (2) while simultaneously positioning different physically present audience groups as protagonists in the strategic change. The paper ends by discussing how the embodiment of these subject positions materializes the change, creating strategic effects and space for making sense of the intended change, and it proposes the notion of “strategic apparatus” for taking the body into account when exploring the socio-materiality of strategic change.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".