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 propose to study the evolution of legal statements that can be found in Web sites. Legal statements are an important part of each Web site because they can be seen as a contract between the owner of the site and its users. For example, a sitepsilas privacy policy explains what kind of data is collected from users by the operator and how it is processed. Operators use terms of use to put restrictions on the conduct of users. In this paper we describe our proposal for a research agenda and methodology that analyzes the evolution of legal statements on the Web. The research agenda argues that studying the content of legal statements and how they change over time allows to analyze and understand the evolution of the Web from different viewpoints. Specifically, changing legal statements allow to identify emerging legal developments, to expose shifting business objectives, and to track the balance of power between operators and users. Our suggested methodology proposes to obtain historical snapshots of Web sites available in the Internet Archive, to group them into different classes, and to analyze the content of the legal document as well as to compute metrics such as size and readability scores. The obtained data can then be used to formulate hypotheses about the evolution of certain characteristics of the Web. We discuss a pilot study that instantiates our methodology. This study is based on five snapshots of 15 different Web sites, and it shows that the methodology is feasible and can generate meaningful results.
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 | 0.000 | 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