Legitimacy and post-conflict state-building: the undervalued role of performance legitimacy
Bibliographic record
Abstract
Legitimacy is essential to state-building after conflict. Yet, the prescribed path to gaining legitimacy is often a narrow one that borrows heavily from the experiences of Western states. Elections are prescribed as an essential first step on the logic that this means gaining process legitimacy can rebuild a social contract between citizens and the state, a social contract that is rooted in democratic norms and values. This article proposes an alternative path, one that emphasises the critical role of performance legitimacy and its non-exclusive nature. Performance legitimacy is granted when citizens perceive that some or all of their basic needs are being met. The article offers a new analytical framework for understanding a state’s potential source of performance legitimacy, how non-state actors may vie with the state to seize this form of legitimacy, and what consequences this has for processes of state institution-building after conflict. In this respect, this article seeks to reorient theory and practice to a broader view of legitimacy and its critical role in post-conflict state-building.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.070 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".