The “Empty-Shell” Approach: The Setup Process of International Administrations in Timor-Leste and Kosovo, Its Consequences and Lessons
Bibliographic record
Abstract
State-building under the aegis of international administrations has faced various hurdles and obstacles in Kosovo and Timor-Leste—failures that came to full light in March 2004 in Kosovo and in May 2006 in Timor-Leste. However, the international conception buttressing the set up of international administrations—I dub it the “empty-shell” approach—is still present in certain policy circles. This article aims to analyze this international conception by clarifying how the UN came to impose its authority over the two territories in a very similar process. While the literature on each state-building experiment is vast and compelling, few authors have attempted to contrast the two case studies, especially regarding the mental conception informing the governance process of these territories since 1999. This article links the empty-shell approach with the delegitimization process that came to be experienced by the UN in both cases. The article describes the international policies put in place by the UN to expand its control over the two territories, a mix of co-option of local elites and the marginalization of the local population. Finally, the article reveals some possible solutions in order to avoid the more blatant difficulties pertaining to state-building conducted from the outside-in.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.044 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".