Faist, Thomas, Margit Fauser, and Eveline Reisenauer, Transnational Migration
Bibliographic record
Abstract
I n Transnational Migration, German sociologists Faist, Fauser and reisenauer provide an introduction to the subject of migration using a transnational lens, focussing on transnational spaces, and outlining transnational methodologies.This book, aimed at senior undergraduate students, goes beyond a review of the existing literature on migration.While, most scholarly work on migration emphasizes the experiences of migrants in their new country, the institutional structures guiding migration, or on the connections of migrants to their country of origin, Faist, Fauser and Reisenauer look to the "multi-sitedness of immigrants" and the continued transactions and relationships between "migrants and nonmigrants across the borders of the state" (1).They offer an evolving and increasingly comprehensive transnational perspective on cross-border migration and its consequences in the twenty-first century, which they call transnationalization.The authors define transnational migration as a perspective focusing on "how the cross-border practices of migrants and non-migrants, individuals as well as groups and organizations, link up in social spaces criss-crossing national states, mould economic, political and cultural conditions, and in turn are shaped by already existing structures" (2).They argue that the transnational approach is a lens, not yet a coherent theory, but that this book represents an attempt to further develop the transnational approach to the study of migration.The transnational focus on non-state actors engaged in cross-border transactions differs from both internationalization in international relations and theories of globalization in that it is multi-directional (not linear) and moves beyond the container of the nation-state without simply dismissing the nationstate in favour of a global or post-national organization.In doing so, the authors focus transnational social spaces, which are spaces consisting of "combinations of ties and their contents, positions in networks and organizations, and networks of organizations that can be found in at least two nation-states" (13).The book is based on three objectives.First, the book aims to provide an overview of transnationality by looking at cross-border ties and
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".