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
Good government requires that laws be expressed clearly. Normative texts serve to integrate within the law a government's policies on social and economic conditions and the rights and obligations of individuals and larger entities. The language of these texts should therefore be precise and easy to understand. But the need for laws to be well written goes well beyond the technical requirements of the legal sphere. For, laws and the language used to express them are directly connected to the everyday practices and general concepts that form the basis of society and civilization. The relationship between laws, language, and society is close and complex. However, few are aware of the high degree to which legislation shapes language, with the result that the impact of legislation on everyday communication tends to be seriously underestimated. Yet, the words, expressions, and underlying concepts used in many areas of human activity are in fact taken directly from or heavily influenced by the very language of the laws that govern these fields. The state therefore has a fundamental obligation to ensure that its legislation is carefully composed, clearly expressed, and of consistently high quality in its language as a whole.
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 | 0.001 | 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