Bibliographic record
Abstract
1. Reconceptualizing Electoral Reform Monique Leyenaar & Reuven Y. Hazan 2. Electoral Reform in Europe since 1945 Alan Renwick 3. The Barriers to Electoral System Reform: A Synthesis of Alternative Approaches Giden Rahat & Reuven Y. Hazan 4. A Conceptual Framework for Major, Minor, and Technical Electoral Reform Kristof Jacobs & Monique Leyenaar 5. The Rise of Gender Quota Laws: Expanding the Spectrum of Determinants for Electoral Reform Karen Celis, Mona Lena Krook & Petra Meier 6. Cultural Explanations of Electoral Reform: A Policy Cycle Model Pippa Norris 7. Electoral reform and Direct Democracy in Canada: When Citizens Become Involved Lawrence LeDuc 8. Party Preferences and Electoral Reform: How Time in Government Affects the Likelihood of Supporting Electoral Change Jean-Benoit Pilet & Damien Bol 9. Democracy as a Cause of Electoral Reform: Jurisprudence and Electoral Change in Canada Richard S. Katz 10. When Electoral Reform Fails: The Stability of Proportional Representation in Post-Communist Democracies Csaba Nikolenyi 11. Veto Players and Electoral Reform in Belgium Marc Hooghe & Kris Deschouwer 12. The Different Trajectories of Italian Electoral Reforms Gianfranco Baldini
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".