Economic Theories of Bundling and their Policy Implications in Abuse Cases: An Assessment in Light of the Microsoft Case
Why this work is in the frame
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Bibliographic record
Abstract
Theories of bundling have had great importance in European competition policy in recent merger control and abuse of dominance cases. Prominent examples include GE/Honeywell, Tetra Laval/Sidel and the recent Microsoft decision. The European Commission has been heavily criticized in all of those cases. In this Paper we attempt to sketch how a systematic approach to bundling cases can be structured. We first provide an overview of existing bundling theories, concentrating on robust economic mechanisms and their empirical implications. This allows us to develop a number of clear criteria to identify potentially anticompetitive bundling. We show that a careful reading undermines recently proposed arguments for a (modified) per se legality rule for bundling.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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