The Availability of Life Jackets in Uncharted Waters: CJEU's Consumer Protection in Crowdfunding
Bibliographic record
Abstract
Crowdfunding is a way of raising money through small contributions from a large number of investors, i.e. crowd. Crowdfunding constitutes a common denominator for number of financing methods, from donations through lending up to venture capital, while all taking place online. Thus, there is a considerable number of legal challenges, namely use of copyright, distribution of loans and credits or possible sale of securities. In many cases the crowd is constituted by large number of consumers, acting outside their trade, business, craft or profession. Yet there are also exceptions. Sometimes, on the other side of the Internet connection sits a professional looking for an investment opportunity instead of an inexperienced consumer. However, which one shall we protect and to what extent? Is there an economic and legal necessity or only an EU urge to protect the consumers even if the protection might not be necessary? Hence, this article analyzes and assesses the current regulatory framework through the lens of CJEU's jurisprudence on the consumer protection with the constant focus on balance of needs and protection of the parties involved.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.028 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".