The International Organization for Migration and the International Government of Borders
Bibliographic record
Abstract
Early debates often read globalisation as a powerful tendency destined to make state borders less pertinent. Recent research has challenged this view by suggesting that globalisation and (re)bordering frequently advance hand-in-hand, culminating in a condition that might be described as ‘gated globalism’. But somewhat neglected in this recent wave of research is the role that particular international agencies are playing in shaping the norms and forms that pertain to emergent regimes of border control—what we call the international government of borders. Focusing on the International Organization for Migration (IOM) and its involvement in the promotion of what it calls better ‘border management’, this paper aims to partially redress this oversight. The IOM is interesting because it illustrates how the control of borders has become constituted as an object of technical expertise and intervention within programmes and schemes of international authority. Two themes are pursued. First, recent work on neoliberal governmentality is useful for illuminating the forms of power and subtle mechanisms of influence that characterise the IOM's attempt to managerialise border policies in countries as different as Armenia, Ethiopia, and Serbia. Second, the international government of borders comprises diverse and heterogeneous practices, ranging from the hosting of training seminars for local security and migration officials to the promotion of schemes to purchase and install cutting-edge surveillance equipment. In such different ways one can observe in very material terms how the project of making borders into a problem of ‘management’ conflicts with a perception of borders as a site of social struggle and politics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".