Bibliographic record
Abstract
In recent years, asylum seekers have made headlines of many newspaper and television reports in European countries and other richer nations around the world, like Canada, the US or Australia. These asylum seekers and refugees are often seen as a problem and a threat to these societies. Reports express fears of huge masses of asylum seekers flooding into countries of the West with governments powerless to stop them. These asylum seekers, they say, are not ‘real’ refugees fleeing violence and persecution, but ‘bogus asylum seekers’ or ‘false refugees’ coming to benefit from the economic and material benefits available in Western states. And particularly since the attacks of 11 September 2001 in the US, and subsequent terrorist attacks in Madrid and London, fears have been raised about the connections that might exist between asylum seekers and terrorists. All of these fears can be argued to be without foundation in fact but they have become part of the everyday understandings of what an asylum seeker is. And at the same time, our televisions and newspapers show us images of refugees massed in camps in Africa, the Middle East or Asia, living in tents, or makeshift shelters, lacking sufficient food supplies, drinking water or basic washing facilities. The people in these camps have fled conflicts, massacres or natural disasters and find themselves still vulnerable and dependent on foreign aid. 1 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.016 | 0.035 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".