Comparative analysis of immigration processes in Canada and Germany: empirical results from case studies in the health and IT sectors
Bibliographic record
Abstract
Twelve qualitative case studies in German and Canadian hospitals and IT companies were used in this mixed-methods study analysing the labour market outcomes of immigrants. The reported case studies investigate the immigrants’ recognition, integration process and the usability of foreign qualifications, skills and work experiences in the labour market. Furthermore, the strategies and rationales of employers and employees within the recruiting process are analysed. Here, the focus lies on the transferability and obstacles of cultural and social capital across country borders as well as the relevant framework conditions. This paper refers to Bourdieu’s approach towards different types of capital as well as the rational choice theory.The results demonstrate that immigrants in both countries face more obstacles accessing the labour market within the health sector than within the IT sector. The context of the recruiting situation strongly affects the strategies and behaviour of the employers or the recruiters. Within these sector- and country-specific confines, individual factors determine the immigrants’ labour market success. Furthermore, the sector and the country affect the relevance of each individual factor in the recruiting process.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".