The Work of Rules: How Organizations Negotiate Rules to Address Disruptions
Bibliographic record
Abstract
While existing research has examined challenges associated with formulating and enacting rules in organizations, less is known about how newly introduced rules evolve and become stabilized in organizations that depend on them. To address this question, we conducted a 2-year ethnographic study that documented the relocation of an emergency department (ED) at a leading University-affiliated hospital in Canada to a new state-of-the-art facility. The relocation changed the patient population, disrupting patient flow practices. To address these disruptions, the ED introduced and negotiated new rules. We traced five rule trajectories, we label emerging, optimizing, reviving, eroding, and materializing, which reflect ED members’ skillful efforts to coordinate and manage overwhelming demands for its services. Our findings suggest that while the deployment of rules improved patient flow, it also unintentionally reconfigured the role relationships among professionals both within and between various units over time. Our study contributes to the literature on organizational rules by providing a processual account of how newly introduced rules evolve and stabilize over time. Contrary to existing coordination research which maintains that rules can either constrain emergent practices or clarify ways of working, our research suggests that rule deployment can yield both productive and counterproductive consequences for coordination practices as rules evolve.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".