Understanding digital nomadism: a three-level framework for migration studies
Bibliographic record
Abstract
As pandemic lockdowns forced traditional office workers to work from home, a subset of these workers left their countries of employment to join a growing movement of location independent transnational digital workers. These digital nomads have captured the imagination of popular media, but academic literature on this topic is still developing. This paper offers a critical review of scholarship on digital nomadism thus far and introduces a sociological framework for situating digital nomadism within migration studies. Building on the analytical tools of lifestyle migration research, we discuss the relationship between digital nomadism and broader processes of neoliberalism and postcoloniality. The paper is based on desk research and a scoping review of existing studies from which it borrows empirical illustrations of digital nomadism. In conclusion, we point to the specific features of digital nomadism that make it distinct from lifestyle and other types of privileged migration and suggest a research agenda for the future.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.008 | 0.043 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".