Bibliographic record
Abstract
This paper tackles the question of how social integration of migrant and native employees takes place in German industry and what role workplace industrial relations play in it. Three company case studies in manufacturing based on expert interviews with management representatives and works councillors, interviews and group discussions with employees of different origin, employee surveys, as well as company statistics, were used to explore this issue. The paper analyzes the social structure of the investigated companies, examines the interaction of employees of different origin and the role workplace industrial relations play in fostering cooperation and social integration. The case studies show that migrants are more likely to be positioned in the lower ranks of the companies’ social structure. Findings suggest, however, that this is primarily a consequence of the migrants having insufficient vocational training, which is probably the result of discrimination outside and at the threshold of the companies rather than a sign of direct discrimination within the companies. Nevertheless, the interviews and surveys show that there is employee resentment against people of different origin. There is a coexistence of resentment on the one hand and good cooperation on the other. Work requirements and the works councils’ and managements’ “internal universalism” (i.e. an orientation towards equal treatment of employees and the interdiction of discrimination within the companies) foster collegial cooperation among employees. German co-determination favours an employee model of interest representation which encourages individuals to choose a work-related identity and labour solidarity to assert their interests rather than identities related to ethnic groups. It is argued that this framework and the daily interaction of the employees eventually evoke feelings of collegiality and foster social integration.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".