Bibliographic record
Abstract
Nobody wants to be seen as soft on crime and illegal immigration. (Former legislative director for Congressman Ed Bryant, (R-TN), Washington, D.C., August 26, 2006) In the early 1990s, widespread anti-immigration backlash propelled the issue of migration control onto the legislative agendas of the German Bundestag and the U.S. Congress. In both countries, public debate was dominated by vociferous claims that the state had lost control over its borders: in Germany, calls for stricter regulation converged on the rapidly expanding number of asylum seekers, whereas in the United States, protests targeted the country's growing population of undocumented immigrants. Importantly, legislators in both contexts were exposed to strong pressures to enact restrictionist immigration reform. This, however, is where the cross-national similarities end. Even though immigration control featured saliently in public debates in both countries – a condition that might lead us to expect corresponding legislative responsiveness (Soroka & Wlezien, 2004) – the outcome of subsequent reform initiatives differed substantially. In Germany, legislators enacted public interest policies – statutes that corresponded to the substantive concerns of the public and that provided for the appropriate measures to achieve their goals. By categorically excluding migrants from certain countries from access to the system, German parliamentarians enacted a drastic measure – even clearing the hurdle of constitutional reform – that succeeded in lowering the number of asylum seekers and defusing widespread anti-immigrant backlash. The U.S. Congress, by contrast, while passing one of the most draconian immigration control bills in the nation's history, eschewed exactly those policy provisions that would have best met public demands for reducing illegal immigration: measures designed to deter the employment of undocumented immigrants. Confronted with opposition by organized interests to stricter worksite enforcement, legislators decided to settle for what I call private interest policies. Skirting measures that would impose concentrated costs on private interests, Congress instead increased control provisions that allowed for credit-claiming without alienating organized constituencies.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".