Conceptualisation of the systemic organisational constellation method and a procedure for its application in coaching
Bibliographic record
Abstract
Systemic constellations are widely used in organisational coaching and consulting to provide a systemic perspective on organisations and teams. However, the method is derived from practical experience and lacks definitional and procedural clarity, which could lead to ineffective application and could hamper quality monitoring and scientific evaluation. Therefore, the aim of this study was to conceptualise the systemic organisational constellation method by developing a shared definition and delivering a procedure for its application. The methodology comprised two parts. First, a clear definition and outline of a procedure for applying the systemic organisational constellation method were formulated through a comprehensive review of the academic literature. Second, this definition and procedure were evaluated using inputs provided by 273 professionals who have used this method. We implemented an online survey between December 2020 and June 2021 to evaluate the definition and procedure, which was subsequently adjusted considering the respondents’ suggestions. The shared definition and procedure resulting from this study may enhance the quality and effectiveness of the method’s implementation, and may clear the way for evidence-based practice.
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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 | 0.094 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".