Open Content Licenses Without Representation: Can You Give Away More Rights Than You Have?
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
Authors who are voluntarily placing their creations into the commons allow the public to build upon their work, sometimes provided that certain conditions are respected. Open content, open source or free licenses intend to facilitate sharing and reuse by lowering transaction costs. In theory, no additional negotiation or copyright or contractual related task is needed to reuse such works because authorization has been provided in advance. However, in practice, it might be uncertain whether all necessary rights have been granted or not. We consider one example of difference between the various copyleft licensing schemes which are available to those who want to place their works or data in a voluntary commons: is the licensor offering the content with a representation that it does not content elements which may infringe upon the rights of third parties, including copyright infringement, privacy, trademark or right to image which might pertain to elements of the licensed work? The article will present the different options and assess the legal consequences of offering representations, or not, and discuss the legal problems raised by waivers of warranties according to EC and national consumer and contract law of European civil law jurisdictions on the one hand, and the perspective of securing sustainable and safely reusable commons on the other hand.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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