Strategic renewal: Beyond the functional resource role of occupational members
Bibliographic record
Abstract
Abstract Research summary In this qualitative study of strategic renewal at a North American news organization we reveal that the treatment of occupational members as resources in strategy literature is necessary, but insufficient. Their activities are critical for organizational survival and competition but also the work needed to maintain their occupational identity. Furthermore, the prevailing research evidence that occupational members impede strategic renewal is incomplete. Our study challenges the narrow view of occupational members as resources that constrain strategic renewal by illustrating how occupational identity “work” is instrumental in facilitating and disrupting strategic renewal. Our findings emphasize the importance of adopting broader definitions of work than the functional definition used in strategic renewal research. We also highlight how the activities of nonmanagerial actors contribute to strategic renewal. Managerial summary During times of change, research highlights how occupational members such as doctors, nurses, engineers, and academics, disrupt and resist change. Our study demonstrates that the same cause of disruption—sustaining their distinctive occupational identity—is critical in facilitating strategic renewal. For managers, we illustrate how and why this occurs and provide practical guidance to leverage this understanding while managing change in occupationally‐dominated organizations.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".