Bibliographic record
Abstract
Suppose that an authoritarian regime wants to make changes to legal norms or institutions to consolidate its hold on political power. Suppose further that the regime in question cannot simply ignore the domestic or international costs of doing so, and that it has an interest in responding to critiques of these changes based on liberal democratic norms and the rule of law. How can it do so? One possible approach is to sow confusion and undermine the normative standards themselves – in effect, to ‘gaslight’ the domestic or international audience (or both). To that end, a regime might assert that the change it proposes resembles a ‘best practice’ from one or more other jurisdictions. Such emulation need not be thorough, or even sincere; it may suffice simply to assert that a proposed change resembles that in a jurisdiction with ironclad rule-of-law credentials. The changes being adopted may bear no real resemblance to the ‘comparators’ on closer examination. Alternatively, the measures being adopted may be similar on their face, but operate in such a different context that they end up serving a very different function to the function they perform in the comparator jurisdiction. Such gaslighting need not succeed in deceiving outsiders or subjects; undermining the standards by which legal reforms are measured, sowing confusion, or providing a superficial pretext for inaction may be sufficient.
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.
How this classification was reachedexpand
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 | 0.001 | 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) | 0.008 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".