Migration, Advanced Digital Technologies, and the Future of Work
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Advanced digital technologies are transforming the way we work, connect, participate, and even live. Their impact is most visible in the migration field where they facilitate decoupling the place of work and the place of residence, potentially leading to whole new opportunities and challenges. Today, digital nomads can travel while they work, while labor migrants, particularly those with temporary status, may find themselves trapped in digital platform work. Contributions to this special Issue shed light on these seemingly opposed phenomena of digital nomadism and migrant worker engagement in digital platforms. This introductory paper offers a critical review of the notion of quality of work, arguing that its contours have been fundamentally shifting in recent times. Empirical insights arising from research on digital platforms (particularly immigrant employment in those) and work on digital nomadism reveal new elements valued by migrant and digital nomad workers. This paper and the other contributions included in this special issue point to the ambivalence of these new configurations, which create vulnerable workers but also agentic subjects who seek to negotiate better career aspirations, whether through digital nomadism or engagement in digital platform work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it