Bibliographic record
Abstract
In North America, the value of the ethnic community is deeply ingrained in national mythology. Ethnic communities supposedly enable immigrants to move from rags to riches, from dishwasher to millionaire. Neither John F. Kennedy nor Al Capone would have risen to the top of their trades without the support of their Irish and Italian communities, which endowed these figures with the best and the worst cultural qualities. In recent decades, however, a counternarrative involving ethnic communities has also appeared in popular mythology. African Americans and Latino communities supposedly keep their members from absorbing the virtues of mainstream society, infecting their members with a culture of despair. The causal link between ethnic community and success or failure seems unquestioned—although the exact processes that supposedly render members of ethnic and immigrant communities inferior remain unsubstantiated. In the labor market, ethnic communities can create opportunities and facilitate segmentation and subordination. For example, information about employment opportunities often travels through ethnic networks and among family members. These opportunities can lead to a comfortable job in corporate banking or to underpaid employment as a maid or a helper in a corner store. Some entrepreneurs may, in fact, recruit workers through ethnic and immigrant networks because community and family linkages result in a particularly vulnerable, yet disciplined, labor force. Whereas the previous two chapters focused on legal and institutional mechanisms of exclusion, the current chapter brings the discussion back to informal processes of distinction and exclusion. As in Vancouver, these less tangible, informal processes operate in Berlin, and they complement legal and institutional processes of subordination that affect immigrant labor. Informal processes of distinction and exclusion affect, in particular, those immigrants who escape legal exclusion because they possess citizenship, such as Spätaussiedler, or they have acquired economic and social rights by living and working in Germany for decades, such as Turkish immigrants. I illustrated in part II how exclusionary processes associated with habitus and embodied cultural capital operate. In this chapter, I focus on social networks, the ethnic economy, and residential immigrant concentration. The North American literature has demonstrated that social networks are of critical importance to the economic well-being of some immigrant groups.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 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".