Host Societies and the Reception of Immigrants: Research Themes, Emerging Theories and Methodological Issues
Bibliographic record
Abstract
Research on the reception and integration of immigrants now recognizes more explicitly the impact that characteristics of societies have as they play host to immigrants. This brief introduction to six papers – by Kasinitz, Mollenkopf and Waters; Boyd; Model and Lin; Borjas; Martin; and Castles – shows how they reflect a research emphasis on four interrelated features of host societies: 1) pre-existing ethnic and race relations, 2) labor markets and related institutions, 3) government policies and programs both for immigration and for broader institutional regulation, and 4) the changing nature of international boundaries, part of the process of globalization. Cultural dimensions permeate analyses of each of these four aspects. Together with others in a larger collection of 18 papers developing this theme (scheduled for publication as a book by the Centre for Comparative Immigration Studies, University of California at San Diego), the various analyses suggest elements useful in constructing a theory of immigrant reception and incorporation taking proper account of the impact of host societies.
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 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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".