The multiple faces of collective responses to organizational change: Taking stock and moving forward
Bibliographic record
Abstract
Summary This special issue focuses on collective responses to organizational change with a goal of enhancing knowledge on the emergence of these higher‐level responses to change. While researchers acknowledge that organizational change inherently involves processes at multiple levels (individual, team, organization), scholars have only recently begun to increasingly promote models of collective responses to change. Spotlighting this gap, in this paper, we explore the dynamic character of collective responses to change, note the multiple ways in which these may develop, and identify theoretical frames rooted in psychology and sociology. This approach contributes to the growing field of responses beyond the individual. Through the papers in the special issue, we offer a framework based on Bourdieu's theory of practice as a platform for bringing together perspectives on agency and structuralism on how responses to change are shaped in the collective. With this framing, we provide direction for future research on successful organizational change through the interrelations between individuals and collectives undergoing change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".