Bibliographic record
Abstract
Purpose This special issue seeks to scope the past, present and future study of those individuals who independently journey abroad for work – the self‐initiated expatriate – a topic which is now attracting increasing attention among management scholars and practitioners alike. Design/methodology/approach This introductory paper takes the form of a brief commentary of the development of the field and a synthesis of the papers in this special edition. Findings Beginning in the late 1990s with a slow trickle of papers exploring the experiences of individuals who had initiated their own expatriation, our understanding of self‐initiated expatriates (SIEs) and self‐initiated expatriation (SIE) has developed exponentially. This development has given rise to a growing awareness of this form of mobility as a potentially powerful force in the increasingly varied global labour market. Yet, as this special issue will argue, there is still a range of conceptual, theoretical and empirical challenges in the study of SIEs, not least of which is a lack of clarity in how the term is used and understood. Despite the expansion of the field, it has hitherto focused primarily on the experiences of professional SIEs moving from and between developed countries. The papers in this issue therefore, address the need for both greater conceptual clarity and for greater empirical diversity. Originality/value The papers included in this special issue each address fundamental issues in the study of the SIE population and offer perspectives that further our understanding of this group and their experiences.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".