Bibliographic record
Abstract
Despite the privilege of German citizenship, Spätaussiedler experience difficulties in the German labor market. Unemployment tends to be high, and many of those who are employed fill positions in the secondary segment of the labor market. A problem for many Spätaussiedler is that their former occupations do not exist or are not in demand in Germany. Tractor operators, technicians in the oil industry, and coal miners from the former Soviet Union have difficulty finding employment in their fields, particularly in Berlin. Other Spätaussiedler still work in their general field, but below their original qualifications. Of these, many are denied work in their former occupations because their foreign occupational and educational credentials are not recognized by German authorities and employers. Government efforts to streamline the transferability of foreign credentials have concentrated on countries within the European Union (Schneider 1995); however, Spätaussiedler from the territory of the former Soviet Union do not benefit from these efforts. Although, as German citizens, they are legally entitled to credential assessment, exclusionary practices in the credential assessment and recognition process still make it difficult for Spätaussiedler to obtain work in the upper labor market segment. These immigrants fall victim to a double standard that values domestic and foreign credentials differently. The nonrecognition of foreign credentials as a mechanism of labor devaluation is not unusual in countries that receive large numbers of immigrants, as illustrated in chapter 5 in the case of immigrants in Vancouver. In Germany, Spätaussiedler present an interesting group because they enjoy citizenship rights and privileges unavailable to other immigrant groups. They receive full legal labor market access, economic integration assistance, the right to credential assessment, privileged treatment by labor market institutions, and, unlike foreigners and naturalized migrants, they are able to use their foreign qualifications to establish small businesses and offer vocational apprenticeships. In some instances, Spätaussiedler even receive preferential treatment relative to other Germans, for example, when applying for small business loans (Juris 2003, BFVG §14). In light of these privileges, labor devaluation through legal exclusion is apparently not an issue for Spätaussiedler.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".