Establishing the Rules of the Game: Election Laws in Democracies
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
Establishing the Rules of the Game: Election Laws in Democracies, Louis Massicotte, André Blais and Antoine Yoshinaka, Toronto: University of Toronto Press, 2004, pp. 191 Whatever one may think of the 2000 American presidential election, it did have one salutary effect: it drew worldwide attention to the importance of fair and impartially applied election laws. The authors of this work needed no such wake-up call; André Blais and Louis Massicotte enjoy a well-deserved international reputation for expertise in this arcane field. But it is likely that their new book, a compendium and analysis of election laws in 63 countries, will attract wider notice because of recent events in the United States. Unfortunately (though understandably), the extreme decentralization and complexity of American election laws prevented the authors from including the U.S. in their comparative database. Happily, the remaining countries in the sample offer more than enough food for thought. The field of election law has been sadly neglected by political scientists and legal scholars (outside the United States); if interest in the topic continues to grow over the coming years, this book should help to nurture a flourishing academic debate.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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