Contract of Mutual (In)Difference: Governance and the Humanitarian Apparatus in Contemporary Albania and Kosovo
Bibliographic record
Abstract
In his book Le malheur des autres, Bernard Kouchner, the founder of Medecins Sans Frontieres and the former French Health Minister, wrote that “[h]umanitarian activities have become customary.” Kouchner’s statement points to the new forms of globally organized power and expertise, located within new transnational regimes, humanitarian networks, non-governmental organizations (NGOs), and multiand bilateral organizations that are now developing. These new transnational regimes, parallel to local forms of rule, constitute a mobile apparatus which I have defined as migrant sovereignties. With the explosive growth of NGOs of all scales and varieties that has occurred since 1945, we are witnessing a massive transformation in the nature of global governance. Such growth has been fueled by the connected development of the U.N. system, and, more particularly, by the increasing global circulation and legitimization of discourse and politics of “human rights.” Resolutions adopted by the U.N. Security Council and various international agencies and meetings show that new forms of sovereignty have come into place alongside older, territorialized forms. These new forms legitimize the right of interference and intervention, identifying a deterritorialized sovereignty that migrates around the globe to sites of “crisis” and humanitarian disaster.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.050 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".