P3P Adoption on E-Commerce Web sites: A Survey and Analysis
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
Privacy is an increasingly important issue for Internet users, especially in the world of e-commerce, where they must disclose large amounts of personal information to make purchases. Various privacy-enhancing technologies (PETs) are currently available, including the platform for privacy preferences project, privacy seals, and human-readable privacy policies. In particular, P3P has been the subject of considerable interest; however, it's also highly dependent on the symbiotic deployment of P3P user agents and policies on vendors' Web sites. Internet users and vendors must commit time and resources to deploy P3P agents or policies, and thus require evidence that the technology won't stagnate or become obsolete. In this article, we survey the current rate of P3P deployment within the e-commerce industry. We also examine P3P's usefulness as a PET, using Everett Rogers' drivers of innovation adoption
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 | 0.003 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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