Liberation Through Narrativity: A Case of Organization Reconstruction Through Strategic Storytelling
Bibliographic record
Abstract
This paper examines the ebb and flow of organizational power and control during an organizational change where a CEO mobilized narratives to liberate his company from top-down control. The emergent conceptual model makes sense of what appears to be discursive disorder – a cacophony of change narratives. Its contribution is twofold. Firstly, by identifying three ‘narratives in the making’ – the initial, counter and corrective narratives, it elaborates the meso-level narrative mechanisms at the heart of discursive struggles during change and extends Boje’s (2010) triad of narrativity. Secondly, it confirms the utility of the ‘organizational becoming’ and CCO perspectives of organizing for understanding 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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".