PayPal is New Money: Extending Secondary Copyright Liability Safe Harbors to Online Payment Processors
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
The Digital Millennium Copyright Act (DMCA) has shaped the Internet as we know it. This legislation shields online service providers from secondary copyright infringement liability in exchange for takedown of infringing content of their users. Yet online payment processors, the backbone of $300 billion in U.S. e-commerce, are completely outside of the DMCA’s protection. This Article uses PayPal, the most popular online payment company in the U.S., to illustrate the growing risk of secondary liability for payment processors. First it looks at jurisprudence that expands secondary copyright liability online, and explains how it might be applied to PayPal. Then it considers legislative proposals and industry-self regulation that similarly target an increasing role for payment processors in the fight against online infringement. It argues that the introduction of a DMCA-like safe harbor for online payment processors offers a fairer and more efficient option for all stakeholders than the status quo of gradually expanding liability risk. It concludes with a discussion of important initial considerations in the design of such a safe harbor.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it