Facebook’s Libra: The Next Tax Challenge for the Digital Economy
Bibliographic record
Abstract
In 2019 Facebook announced its plan to launch a cryptocurrency within the coming year, with the express goal of extending past its existing user base to those who lack access to traditional banking services. The prospect of Facebook enabling millions of global transactions outside of the (highly regulated) conventional banking system prompted scrutiny, most immediately in the area of financial services regulation. But it should also heighten the sense of urgency to reconstruct prevailing global tax rules to ensure that highly digitalized businesses pay an appropriate amount of taxes wherever they carry out business activities and create value. This paper lays out Facebook Libra’s original design concept, the problems it sought to solve, and the potential implications its successful launch would have on the redesign of the global tax system that is already in progress. The paper concludes that the current global economic turmoil makes for an uncertain future, but one that will clearly require a coherent strategy for taxing high tech firms and innovations with global scope, with Libra a prominent case.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.009 |
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".