Transatlantic Perspectives on Citizenship and Diversity: An Introduction
Bibliographic record
Abstract
While the movement of people is not new, international migration is gaining more importance in today's globalized world.New and faster means of communication and transportation connect people around the world in completely new ways.Ever increasing numbers of people are leaving their home countries and moving to foreign destinations to escape from hunger, persecution, war or environmental catastrophes; they migrate to seek a better life, find employment, study, enhance their careers or life styles, or to join a partner or family members who already live abroad.With increasing numbers of people being internationally mobile, ethnocultural diversity, integration, as well as (lived and formal) citizenship have become some of the most important topics in scholarship and policymaking alike.While it used to be popular to differentiate between Europe's "traditional nation-states" and the "settler societies" of the New World (Milich and Peck 1998), over the past years, scholars have noticed a convergence of immigration and citizenship policies on both sides of the Atlantic (Dauvergne 2016; Joppke 2007; Joppke 2010; Triadafilopoulos 2012).According to one commentator, this development has even led to the "end" of settler societies (Dauvergne 2016).In what follows, we briefly survey the literature that supports the claim that the countries on both sides of the Atlantic are moving closer together in their treatment of immigration, diversity and citizenship (convergence theory).We then circumscribe the goals and caveats inherent to conducting transatlantic comparisons.Finally, we provide an overview of the contributions to this special issue.Scholars examining immigration and citizenship policies in Western democratic states on both sides of the Atlantic often refer to Germany and Canada.These two countries tend to be portrayed as being located at opposing poles of the definitions of nationhood and, thus, of immigration, integration, and citizenship policies (Bauder 2011;Brubaker 1989).Existing differences notwithstanding, scholars like Triadafilopoulos (2012), Winter (2014), Schmidtke (2014), and Kolb (2014) underline the increasing convergence of both countries' immigration, citizenship and integration policies.Triadafilopoulos (2012), for example, holds that despite different national histories and approaches to migration, Canada and Germany have come to address questions of immigration and membership in strikingly similarand increasingly multiculturalways.This may be due to the fact that the migration and integration management in both countries, while being caused by different circumstances, has increasingly shifted to 1
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".