Taking More than They Give: MNE Tax Privateering and Apple's “Ocean” Income
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
Following a three-year investigation, on August 30, 2016, the European Commission (EC) released its decision in the Ireland-Apple State aid case. The EC found that Ireland had breached the Treaty on the Functioning of the European Union because the manner in which Ireland had determined the tax payable by two Apple subsidiaries was not consistent with the arm's length principle and/or it was not based on objective criteria. This meant that Ireland had selectively favored Apple and provided the firm with State aid. The EC decision provides an example of how aggressive multinational enterprise (MNE) tax minimization is anti-competitive. The Ireland-Apple case also provides an illustration of how a lack of transparency and incoherency in MNE definition contribute to aggressive MNE tax minimization. States' reactions to the EC decision are further telling because they show how MNE tax minimization engages the self-interest of States. This suggests that efforts to combat aggressive MNE tax minimization, such as the OECD's Base Erosion and Profit-Shifting Action Plan, face complex State motivations in effecting change on the international level. Profit haven States have the most to lose if MNE tax minimization is effectively addressed. In addition, MNE home States may be at times loath to support changes to the system which favors “their” MNEs at the expense of other States' tax revenues. It is as if some home States view MNEs as their privateers, with such MNEs operating internationally under the tacit approval of their home States to aggressively avoid paying taxes to other countries. Home State leadership may be mistaken in thinking that MNE tax minimization is in their favor because MNEs are largely free agents and aggressive MNE tax minimization is dearly costing nearly all states.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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