Introduction: Bureaucratic Routes to Migration: Migrants' Lived Experience of Paperwork, Clerks, and Other Immigration Intermediaries
Bibliographic record
Abstract
For a number of migrant actors, bureaucratic processes related to immigration constitute the greater part of the route toward their aspired destination and significantly shape their experience of migration and forced immobility. This special issue takes a look at the meaningful ways in which migrant actors interact with immigration bureaucracies and at how administrative procedures, with their highly emotional potential, shape in turn the subjectivity, decisions and actions of migrant actors. All the articles here analyse immigration bureaucracy as a dynamic process mediated by a network of people and by material objects (for example, documents, forms). Whether work, marriage or refuge is the reason for migration, the period of waiting in administrative limbo — which can last years — is crucial to our understanding of the bureaucratic encounter as a social force. This issue, dedicated to migrants’ lived experience of paperwork, clerks and other immigration intermediaries, explores two aspects of migrant actors’ encounters with immigration bureaucracies that go beyond the specificities of each individual’s personal background and trajectory: the production of affects and bureaucratic agency; the former often being the driving force behind the latter.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".