Off the Rails: The Erosion of Guardrails and Institutional Complexity States in Hybrid Organizations
Bibliographic record
Abstract
Recent research on hybrid organizations has begun to adopt a dynamic perspective, recognizing that the salience of embedded logics vary over time and that guardrails play an important role in resolving institutional complexity tensions and maintaining a unique institutional order. However, hybrid literature has yet to fully reason with the cases where hybrids repeatedly fail and entirely change form. Drawing on event sequencing and temporality literatures, we theorize how endogenous and exogenous pressures can lead to fundamental changes in the nature of institutional complexity within hybrid organizations over time. Extending the guardrails concept, we develop the concepts of friction events, which erode guardrails and adjust the salience of institutional logics embedded in the organizations, and rupture events, which destroy guardrails and lead to a fundamental realignment in institutional logics. With this approach, we theorize changes in institutional complexity states and develop a model which helps explain shifting patterns amongst hybrid organization logics over time. As a whole, this paper extends emerging literature on guardrails and builds a stronger temporal understanding of hybrid organizations and institutional complexity.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".