Offshore Finance and Global Governance: Disciplining the Tax Nomad
Bibliographic record
Abstract
I stumbled across the term ‘nomad millionaire’ in Ronan Palan’s 2003 book on The Offshore World. In this opportune text, Vlcek uses this increasingly maligned term to describe a growing and assorted cluster of individuals and firms who seek to minimise, and possibly completely avoid and stamp out, their tax obligations among multiple jurisdictions; leaving most of us, taxpaying residents, to foot the bill of massive public debt. The most powerful asset in their arsenal is not simply the significant wealth and financial capital that these persons (real or corporate) have amassed, and its political leverage, but the mobility with which they graft their assets, enabling a strategic determination of when and where to place which portion of their money and for how long. The mobility of their liquid resources, and at times of themselves, is so extensive that it effectively lacks domicile. Nomadism has taken mobility to a higher level. And globalisation and the digital economy (and now crypto-currencies?) have given bold wings to tax minimisation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".