No End In Sight: How regimes form barriers to addressing the wicked problem of displacement
Bibliographic record
Abstract
Wicked problems are complex and dispersed challenges that go beyond the capacity of individual organizations and require a response by multiple actors, often in the form of transnational regimes. While research on regimes has provided insights into such collective responses, less is known about how such regimes may form barriers that hinder and block appropriate responses to addressing wicked problems. Exploring the problematic role of regime-level responses is timely given that many of today’s wicked problems are far from being alleviated and in many instances appear instead to be intensifying. We draw from complementary insights of regime theory and research on institutional barriers to explore our research question: How do regimes form barriers to addressing wicked problems, and which mechanisms sustain such barriers? We explore this question with a longitudinal case study of the transnational regime for refugee protection and its response to displacement in Rwanda. From our findings, we develop a model of dissociation that explains how actors move further away from addressing a wicked problem. We identify four dissociative mechanisms (discounting, delimiting, separating, and displaying) that each create a distinct regime-level barrier. These barriers are distributed and mutually reinforcing, which makes it increasingly hard for actors to find alternative ways of responding to an escalating problem. Our study provides insights for research on regimes and wicked problems as well as studies on institutional barriers. We conclude with policy implications for overcoming those barriers, in line with the wider concerns and motivations of this special issue.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".