Managing Change in Pluralistic Organizations: The Role of Normative Accountability Assumptions
Bibliographic record
Abstract
Pluralistic organizations face the challenge of managing the co-existence of multiple sets of assumptions associated with each institutional logic. This multiplicity of assumptions problematizes the findings from the change management literature that for successful change management, the normative assumptions of the change initiative should be congruent with the organizational normative assumptions. One of the organizational mechanisms in which the normative assumptions are encoded and enacted is the system of accountability, hence in pluralistic organizations, there is a need to understand the role of the interplay of the normative accountability assumptions of the change initiative with the multiple sets of accountability assumptions representing individual logics within the organization. This study examines the case of a project to renew a strategic framework of a Canadian public university. The project diverged from the existing governance practices and their associated accountability assumptions that represented the institutional logic of managerialism. We found that this project was widely accepted, despite deviating from the institutional logic that supported existing practices, because its accountability assumptions were congruent with co-existing and deeply-rooted, democratic logic within the organization. Our findings contribute to the change management literature by highlighting the role of normative accountability assumptions in change management within pluralistic 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 | 0.071 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.056 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".