Bibliographic record
Abstract
Abstract The rise of populist political rhetoric signals a departure from accepted models of democratic representation. Nowadays, in Israel and in other democratic countries, many elected officials purport to give effect to the raw convictions of their constituents. We contend that calls for elected officials to mirror popular views undermine democratic representation. In addition to the theoretical challenges it faces, the narrative of mirroring public sentiment has the potential to disguise what might be the underlying intent of populist politicians—to actively manipulate the political agenda and reshape popular preferences, while passing these off as reflecting the public’s authentic convictions. We call this “false mirroring.” Populist rhetoric has also spilled over into the judiciary. Some judges embrace public opinion, incorporate it into their decision-making and, in doing so, generate populist courts. This article examines Israeli case studies in order to expose the unsettling role of populist rhetoric in both political and judicial contexts. Judges, we suggest, must continue developing tools to resist judicial populism and maintain robust and independent courts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".