IMIS-Beiträge Heft 40 - Special Issue: The New Politics of International Mobility. Migration Management and its Discontents
Bibliographic record
Abstract
Martin Geiger and Antoine Pécoud: The New Politics of International Mobility. Migration Management and its Discontents.; Bimal Ghosh: A Snapshot of Reflections on Migration Management. Is Migration Management a Dirty Word?; Juan M. Amaya-Castro: Migration and the World of Work: Discursive Constructions of the Global in ILO Narratives about Migration; Sara Kalm: Global Migration Management, Order and Access to Mobility; Catherine Wihtol de Wenden: Globalization and International Migration Governance; Doris Hilber and Tatjana Baraulina: Migration and Development. A New Policy Paradigm in Germany?; Victor Piché: In and Out the Back Door: Canada’s Temporary Worker Programs in a Global Perspective; Clotilde Caillault: The Implementation of Coherent Migration Management Through IOM Programs in Morocco; Hideki Tarumoto: Towards a New Migration Management: Care Immigration Policy in Japan; Bernd Kasparek and Fabian Wagner: Local Border Regimes or a Homogeneous External Border? The Case of the European Union’s Border Agency Frontex; Fabian Georgi and Susanne Schatral: Towards a Critical Theory of Migration Control: The Case of the International Organization for Migration (IOM); Duncan Cooper: Conference and Workshop Report
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.236 | 0.106 |
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".