Conceptualising ‘Meta-Work’ in the Context of Continuous, Global Mobility: The Case of Digital Nomadism
Bibliographic record
Abstract
Meta-work – the work that makes work possible – is an important aspect of professional lives. Yet, it is also one that remains understudied, in particular in the context of work activities characterised by continuous and global mobility. Building on a qualitative approach to online content analysis, this article sets out to explore the meta-work underlying digital nomadism, a leisure-driven lifestyle premised on a ‘work from anywhere’ logic. This article explores the four main dimensions of meta-work (resource mobilisation, articulation, transition and migration work) of digital nomads. In doing so, it shows the distinctiveness of the meta-work activities of digital nomads, thus conceptualising meta-work in the context of continuous, global mobility. Importantly, this article also challenges mainstream depictions of digital nomadism as a glamorous lifestyle accessible to anyone with the ‘right mind’ and the willingness to work less, be happier and live in some far-away paradisiac setting.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.052 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".