Bibliographic record
Abstract
The central concern of this book is to find answers to fundamental questions about the British asylum system and how it operates. Based on ethnographic research over a two-year period, the work follows and analyses numerous asylum appeals through the British courts. It draws on myriad interviews with individuals and a thorough examination of many state and non-state organizations to understand how the system works. While the organization of the book reflects the formal asylum process, a focus on specific legal appeals reveals the ‘political’ factors at play as different institutions and actors seek to influence judicial decision-making and overturn/uphold official asylum policy. The final chapter draws on the author’s ethnographic findings of the UK’s ‘asylum field’ to re-examine research on the Refugee Determination System in the US, Canada and Australia which has narrowly focused on judicial decision-making. It argues that analysis of Refugee Determination Systems must be situated and studied as part of a wider, political, semi-autonomous ‘asylum field’ which needs to be better understood. Providing an in-depth ethnographic study of a national asylum system and of immigration law and practice, the book will be an invaluable resource for academics, researchers and policy-makers in the UK and beyond working in this highly topical area.
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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 | 0.001 | 0.003 |
| 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 | 0.015 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".