Incorporation policies, identity, and relationships between host societies and immigrants
Bibliographic record
Abstract
Immigration and the diversity it creates are at the heart of numerous debates in most Western liberal democracies. In order to manage this influx of newcomers, countries have chosen different strategies with different consequences. This dissertation considers the role of these strategies, specifically incorporation policies---policies whose goal is to incorporate immigrants in their new society---in the development of intergroup attitudes. It differs from past research by looking at the relationships between these policies on both hosts' and immigrants' attitudes. In doing so, it also argues for the inclusion of context when studying immigration attitudes and their causes. The central question addressed here is whether some institutional arrangements are more likely to foster relationships between host societies and immigrants where both groups do not feel threatened by the other. This question is answered in three distinct studies each addressing different aspects of it, thus providing a more integrated view of these relationships. The first paper compares immigrant's identification and acculturation orientations among ten immigration countries while the second considers the relationship between incorporation policies and cultural threat among host societies in 17 countries. The third paper focuses on a particular case, Canada, and tests whether diversity and ways of managing it can serve as building blocks for a transformed national identity. Using observational and experimental data from three different datasets, the following studies establish a series of important findings including : (1) there is no difference across policy regimes in ethnic identification, immigrants in every policy regimes tend to identify more with their ethnic group than with the majority; (2) only countries with open incorporation policies are able to foster integrationist attitudes among ethnic identifiers; (3) among host societies, open citizenship policies are associated with less cultural threat but multiculturalism policies are not; (4) citizenship policies also mitigate the effect of threat on anti-immigration attitudes, while more comprehensive multiculturalism policies have the opposite effect; (5) contrary to past research on priming of national identity, raising the salience of Canadian identity does not make Canadian respondents more opposed to immigration, in some instance it even makes them more acceptant of it.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".