Bibliographic record
Abstract
While the flow of refugees and asylum seekers from the Middle East and North Africa continues into Europe unabated, the war of words within their intended destination countries escalates.Practical concerns about the ability of European destinations to manage the large numbers of arrivals are being supplanted by concerns over social cohesion and, especially since the attacks on Paris, security.Public figures and members of the public alike have voiced worries over who is coming, whether they are refugees, economic migrants, or potential terrorists.The term 'refugee' itself has taken on widely differing connotations, invoking deep sympathy from some, scepticism from others, fear from others.It is rarely acknowledged that 'refugee' serves as a label to be attached to individuals, and that this label is not value-neutral.In this first issue of 2016, Bernadette Ludwig asks us to pay more attention to the labelling of persons as refugees, noting that for some the label confers advantages but that others wear it as a burden that they would prefer to shed.Much of this issue is devoted to the different modes of migration to which our authors devote their attention.The flight of refugees and asylum seekers from danger is covered by Ludwig and by Francesco Vecchio who looks at how asylum seekers in Hong Kong take advantage of that city's status as a global city.Living there, even as an undocumented migrant, offers the advantages of global interconnections that support economic activity across borders, resulting in asylum seekers making net contributions to Hong Kong's already vibrant economy.We learn from Kyungran Roh and Romee Lee that being a defector, although potentially a symbol of political advantage for the receiving society, brings with it liabilities in the labour market of South Korea whose modern economy requires skills that few defectors possess.South Korea is urged to take the unique needs of North Korean defectors into account in the services that they provide.Staying in Asia, Rezaul Islam and Stefan Cojocaru help us to understand the contemporary challenges of migrating as a domestic worker, particularly challenges that the ILO's Domestic Workers Convention of 2011 was to guide receiving states through.But the goal of decent work for all domestic workers is yet to be realized owing to uneven adherence to its principles across Asia.Spain, like some other European countries, has experienced a reversal of fortunes, now as a receiving society whereas it previously was a net emigration country.Perhaps better known as a destination for migrants from sub-Saharan Africa, Mar ıa Hierro shows us it has become a major draw for Latin Americans aspiring to a better life in a country that shares their language.The United States, now the world's second largest country after Mexico of those who speak Spanish, attracts large numbers of undocumented Honduran migrants.Jana Sladkova describes the challenges of their journeys as well as of their lives as undocumented migrants in a society increasingly uneasy with their presence.Blessing Uchenna Mberu and Roland Pongou take us to Cameroon to explore the many facets of the highly dynamic migration, both internal and international, in this under-studied country.Timothy Mechlinski offers a theoretical advance in our understanding of migration by looking at the important role of transportation workers in Burkina Faso, Côte d'Ivoire, Mali, and Ghana.Mechlinski, who covered thousands of miles of travel in those countries, brings us a rich account
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.252 | 0.145 |
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".