The Legislative and Institutional Structure of EU Electronic Communications Regulation
Bibliographic record
Abstract
The development of the Internal Market has been one of the \nEuropean Union’s (hereinafter \nthe ‘ EU greatest projects. The goal of the Internal Market is to increase economic \nprosperity among the EU’s Member States by reducing the barriers to trade and \ninvestment. The cornerstone s of the Internal Market are the Four Freedoms. These \nfreedoms establish the free movement of people, services, goods and capital and are \nenshrined in the Treaty on the Functioning of the European Union (hereinafter the \n'TFEU'). With greater economic integration, Member States have begun to reap the benefits of \nincreased trade and investment. With regards to the Internal Market, an important \ninitiative for the Commission is the liberalisation and harmonisation of the electronic \ncommunications sector. This initiative promotes the free movement of communications \nservices across the Member States. The communications sector has become a priority \nbecause an advanced communications infrastructure is necessary in order to develop a \ndigital knowledge based economy. The Commission has identified the transition to such an \neconomy as integral to the future economic and social prosperity of the EU.
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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 | 0.053 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".