Patērētāja lēmuma autonomijas ievērošana digitālajā vidē: pierādīšanas pienākums
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
In the last decade, the digitalization of the consumer market has given opportunities to performer of commercial practices to effectively influence the autonomy of the consumer’s decision. The digital economy has developed many different types of commercial practices that nudge consumers to make transactional decisions that are contrary to their interests, such as dark patterns. Currently, the most important legal instrument for the protection of consumer decision autonomy in the European Union is the regulation of the prohibition of unfair commercial practices. However, the new challenges reduce the effectiveness of regulation. The article analyses one of the current legal problems – the compliance of the burden of the proof model with the reality of the digital environment. The article argues that the model is not suitable for ensuring a high level of protection of consumer decision autonomy in the digital economy, therefore the regulation of the unfair commercial practices’ prohibition should be changed radically.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.041 |
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