Reimagining Migration Through a Holistic Lens
Bibliographic record
Abstract
Most developing societies are ageing rapidly, and the sharp decline in fertility is further accelerating the multifaceted social and economic challenges (Kiss et al., 2022). High-skilled migration is being pursued by many countries as an essential solution to these challenges (Adezza & Pazzona, 2022; Kvashnin, 2022; Zimmermann, 2009; Kahanec & Zimmermann, 2010; Ruhs, 2011). Highly-skilled migrants (HSMs) can fill labor market gaps across sectors, contribute to pension funds, and bring valuable expertise and innovation, as well as enrich the sociocultural life in the host societies (Kahanec & Zimmermann, 2008; Bonin et al., 2008). HSMs’ contribution is critical to the long-term viability of vital public services and social welfare systems, while enhancing productivity and competitiveness across various sectors. However, the overarching legal frameworks for attracting skilled professionals, often approach the social and geographical mobility of the skilled workers with a narrow vision. Mobility is typically seen as driven solely by the HSM's career goals, without consideration of the broader social and cultural contexts HSMs exist within. Such views are critical for attracting migrants; however, they fall short in addressing the retention of HSMs, which is much more complex as it deeply entangled with the migration experience. HSMs are not simply a resource, they are complex individuals with career, social, cultural, and personal aspirations, wishes, and desires. In this symposium, we aim to reimagine the retention of HSMs by approaching at the migration experience from a multidimensional perspective. We aim to advance our holistic and humane understanding of the complexities involved in migrants' professional and personal lives. Through a holistic lens, we examine the individual level, where personal attributes such as skills, motivations, career aspirations, and psychological well-being are considered alongside the organizational level, focusing on workplace practices, organizational culture, professional networks, and support systems that affect further inclusion and career advancement. This does not happen in a social vacuum but requires exploration of aspects eralting to the broader socio-cultural, economic, political, and legal domains in connection with the larger cosmopolitan context in which the migrants exist including work-life balance, membership to communities, and status and condition of their families. Reconstructing Positive Self in Times of Indeterminate Conflict among Russian High-Skilled Migrants Author: Mark Van Der Giessen; Author: Sofia Villo; Author: Alexei Koveshnikov; Aalto University Highly Skilled Migrants’ Career Adaptability Strategies for building Sustainable Careers in Norway Author: Sahizer Samuk Car; BI Norwegian Business School Author: Linde Maria Willgren Dyrud; BI Norwegian Business School Author: Sara Solberg Larsen; Intermediaries in Cross-Border Staffing: Temporary Work Agencies Author: Kornelia Anna Kerti; Tilburg University Author: Brigitte Kroon; Tilburg University Author: Inge Bleijenbergh; Radboud University Nijmegen The role of physical and virtual cosmoscapes in enabling integration Author: Eriikka Paavilainen-Mäntymäki; University of Turku Author: Tiina Anna-Maria Ritvala;
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.038 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".