How Recent Amendments in German Immigration Law Affect Decisions: The Case of Polish Doctors
Bibliographic record
Abstract
Introduction The potential of a managed immigration to Germany due to economic reasons was for a long time ignored by German politicians. They claimed that Germany was not a country of immigration at all. For example, the German social democratic party (SPD) agreed in 1982 that the Federal Republic of Germany was not an immigration country. In 1994 the conservatives (CDU/CSU) made clear that their party would never adopt a German immigration law (Marshall 2000: 13, 155). This situation lasted until 2000, when the German chancellor Gerhard Schro¨der announced the decision to establish a German version of the American ‘green card’ and thereby initiated a discussion about managing the inflow of immigrants due to economic reasons. As a result, German Minister of the Interior Otto Schily declared that Germany would establish the most progressive immigration law in the European Union (EU). Immigrants should be selected on the basis of a point system, which is used in typical immigration countries such as Canada or the US. In this way, Germany would be selecting its immigrants according to demographic needs and labour market demands. The pointbased system was not introduced due to political tactics. Almost at the same time (beginning on 31 March 1998), the negotiations for the accession of Poland as a new member of the EU took place. The moot point has been the question as to whether Polish citizens wishing to work in other countries should be allowed to move freely within the EU. Germany only accepted Poland as a new EU member after being allowed to restrict the freedom of movement within the EU for those Polish employees willing to migrate to Germany. Germany took the chance to exercise this option: Polish employees will not be allowed to work in Germany until the year 2009 (Ullrich & Rudloff 2004: 173-177; Bundesregierung 2006). Simultaneously, professional associations stated that Germany was starting to run out of doctors, something Great Britain, for example, had experienced in the past. This development was broadly covered and enlivened by the media. Great Britain had embarked on a clear strategy: ‘Poles fill holes’ announced the Department of Health (2005) referring to the fact that Polish doctors could be attracted for the British health system.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".