Winning, Losing, and the Quality of Democracy
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
Citizens who voted for a party that won the election are more satisfied with democracy than those who did not. This winner–loser gap has recently been found to vary with the quality of electoral democracy: the higher the quality of democracy, the smaller the gap. However, we do not know what drives this relationship. Is it driven by losers, winners, or both? And Why? Linking our work to the literature on motivated reasoning and macro salience and benefiting from the Comparative Study of Electoral Systems project—covering 163 elections in 51 countries between 1996 and 2018, our results show that the narrower winner–loser gap in well-established electoral democracies is not only a result of losers being more satisfied with democracy, but also of winners being less satisfied with their victory. Our findings carry important implications since a narrow winner–loser gap appears as a key feature of healthy democratic systems.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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