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 metaphors we use to imagine, describe, and regulate new technologies have profound legal implications. This article offers a critical examination of the metaphors we choose to describe encryption technology and aims to uncover some of the normative and legal implications of those choices. The article begins with a basic technical backgrounder and reviews the main legal and policy problems raised by strong encryption. Then it explores the relationship between metaphor and the law, demonstrating that legal metaphor may be particularly determinative wherever the law seeks to integrate novel technologies into old legal frameworks. The article establishes a loose framework for evaluating both the technological accuracy and the legal implications of encryption metaphors used by courts and lawmakers—from locked containers, car trunks, and combination safes to speech, shredded letters, untranslatable books, and unsolvable puzzles. What is captured by each of these cognitive models, and what is lost?
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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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