Combining Process Consultation and Structural Interventions
Bibliographic record
Abstract
This article explores the compatibility of a process consulting stance with structural interventions intended to promote significant organizational redesign. Much of the existing literature on process consultation implies that this capacity‐building approach is best suited to relational or process concerns. However, Edgar Schein and other recent commentators have observed that structural issues are not precluded from its purview. Through a case study involving a process consulting stance in relation to a shifting range of structural concerns, this paper argues that the latter offers a feasible way of pursuing structural change. We also show that models focusing on structure allowed us to generate questions for our inquiry process. However, the paper also suggests that it is important to underpin the intervention with a sound grasp of the purpose and affordances of specific structural theories and to be watchful for the significant reserves of resistance that can be aroused when structural issues are tackled. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".