A Survey and Analysis of the P3P Protocol's Agents, Adoption, Maintenance, and Future
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 this paper, we survey the adoption of the platform for privacy preferences protocol (P3P) on Internet Web sites to determine if P3P is a growing or stagnant technology. We conducted a pilot survey in February 2005 and our full survey in November 2005. We compare the results from these two surveys and the previous (July 2003) survey of P3P adoption. In general, we find that P3P adoption is stagnant, and errors in P3P documents are a regular occurrence. In addition, very little maintenance of P3P policies is apparent. These observations call into question P3P's viability as an online privacy-enhancing technology. Our survey exceeds other previous surveys in our use of both detailed statistical analysis and scope; our February pilot survey analyzed more than 23,000 unique Web sites, and our full survey in November 2005 analyzed more than 100,000 unique Web sites.
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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 | 0.002 | 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 | 0.001 | 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