The Dynamics of Client-Consultant Relationships: Exploring the Interplay of Power and Knowledge
Bibliographic record
Abstract
In this paper, we investigate the dynamics of client-consultant relationships and analyze how power and knowledge are shared and negotiated between consultants and clients during the implementation of configurable technologies. Empirical evidence is provided by three case studies representing three classic types of client-consultant relationships. We draw on two complementary perspectives: possession view (i.e., power and knowledge are based on resources that can be owned or controlled by individuals) and practice view (i.e., power and knowledge are relational in nature and exercised in action). The paper develops a framework that shows that power and knowledge are closely intertwined and that the possession and practice views are complementary in understanding configurable technology projects. The paper also demonstrates the importance of the initial set-up of the project and how knowing/powering mechanisms can reinforce or change implementation trajectories, which, in turn, can affect project results.
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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 | 0.020 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".