Design Performances: How Organizations Inscribe Artifacts to Change Routines
Bibliographic record
Abstract
Organizations often create and employ artifacts in order to change their routines, but little is known about how artifacts can be designed to intentionally influence routine dynamics. In this paper, I present findings from an inductive, ethnographic study of how a law enforcement agency fabricated a game-theoretic artifact to modify its patrolling routine. Based on my in-depth analysis of the actions associated with creating this game-theoretic artifact, I develop a theoretical model that shows how organizational actors iteratively engage in a series of design performances to envision new sociomaterial assemblages of actors, artifacts, theories and practices. These design performances influence routine dynamics by both eliciting mechanisms of abstracting grammars of action, exposing assumptions, distributing agency, and appraising outcomes and by creating new assemblages that can be deployed in future routine performances. By revealing the generativity of design performances and sociomaterial assemblages, this empirical study contributes to our understanding of routine dynamics, performativity, and strategy tools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".