Dynamic properties of successful plural leadership configuration: An exploratory process-study
Bibliographic record
Abstract
Our article introduces an exploratory process study of successful plural leadership configuration in searching for alternative solutions to wicked problems. The study was executed within four educational organisations that solved challenging wicked problems arising from today’s changing contexts. We argue that plural leadership configuration is a dynamic process when people in diverse organisational positions, roles, and levels design profitable endeavours through their ideas and activities, bring about desirable outcomes within diverse conditions and outline the future. We searched for potential systemic patterns, characteristics, and structure within this dynamic process. To find these properties, we exploited the theoretical concept of an event that corresponds to organisational experiences in terms of people, ideas, activities, conditions, and outcomes. We presumed that the systemic properties could be found through events’ interaction that is proved to be dynamic. Consequently, we exploited dynamic system theories and studied chains of succeeding events and their agglomerations. As a result, we determined properties that were generalisable across the four organisations. The main results indicated that to find alternative solutions to wicked problems, a strong connection between activities and ideas was crucial. However, committed people were needed as moderators between them. Focusing only on conditions such as plans or new programmes, did not bring about successful solutions.
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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 | 0.016 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".