Digital Nomads and Settler Desires: Racial Fantasies of Silicon Valley Imperialism
Bibliographic record
Abstract
This paper investigates the coloniality of contemporary digital nomadism, an identity that numerous Western tech workers use to describe lifestyles of location independence in which they travel the world while maintaining Silicon Valley salaries. Specifically, I assess colonial genealogies of digital nomads and more problematically defined “digital Gypsies.” It was during the height of 19th-century Western European imperialism that Romantic Orientalist texts proliferated, celebrating the racial and sexual “free and wandering Gypsy.” This deracinated figure was used to allegorize colonial desires and imperial violence alike. As I suggest, nomadic racial fantasy undergirds contemporary freedom desires today emergent from the heart of a new empire—that of Silicon Valley. In describing Silicon Valley imperialism and its posthuman digital avatar, I assess how nomadic fantasy transits technologies of gentrification into new frontiers. For instance, sharing economy platforms such as Airbnb celebrate the digital nomad, bolstering contexts of racial dispossession while continuing to deracinate Roma lifeworlds. Might nomad exotica in fact index coloniality and its ability to traverse time and space? How has this fantasy been abstracted over time, also entangling with posthumanist nomadic onto-epistemologies?
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".