Sample Surveys and Population Censuses as Data Sources on the Second Generation of Migrants: Foreign Experience
Bibliographic record
Abstract
The increasing role of migration in the world makes the integration of migrants into host societies a crucial social process. In the long run, integration is closely related to the topic of the second generation of migrants and their relative well-being in society. In Russia, which attracts a large number of migrants, the integration of the second generation is also very important but the understanding of it is fragmented due to the small number of relevant studies. The task of obtaining relevant data on migrants' descendants and their participation in social and economic life requires taking into account the wealth of foreign experience in studying this topic. This paper provides an overview of approaches to the study of the second generation of migrants in the United States, Canada and Western European countries. The review is based on analytical and methodological publications of national statistical agencies and international organizations (UN, OECD, Eurostat), metadata from special sample surveys and a number of academic articles. The authors discusses the main data sources used to estimate the number of second-generation migrants and to provide information on their socio-economic characteristics, such as censuses and microcensuses, regular labour force surveys and ad hoc sample surveys. The article describes nuances in the definition and evolution of the concept of «second generation» in the national statistical systems. The results of studies on the social mobility of descendants of immigrants are summarised. In conclusion, we offer practical recommendations for modernizing the system of statistical recording of migration in Russia based on the long-term foreign experience of studying the second generation of migrants.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".