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
Abstract Democratic elections are designed to create unequal outcomes—for some to win, others have to lose. This book examines the consequences of this inequality for the legitimacy of democratic political institutions and systems. Using survey data collected in old and new democracies around the globe, the authors argue that losing generates ambivalent attitudes towards political authorities. Because the efficacy and ultimately the survival of democratic regimes can be seriously threatened if the losers do not consent to their loss, the central themes of this book focus on losing—how losers respond to their loss and how institutions shape losing. While there tends to be a gap in support for the political system between winners and losers, it is not ubiquitous. The book paints a picture of losers’ consent that portrays losers as political actors whose experience and whose incentives to accept defeat are shaped both by who they are as individuals as well as the political environment in which loss is given meaning. Given that the winner-loser gap in legitimacy is a persistent feature of democratic politics, the findings presented in this book have important implications for our understanding of the functioning and stability of democracies since being able to accept losing is one of the central, if not the central, requirement of democracy. The book contributes to our understanding of political legitimacy, comparative political behaviour, the comparative study of elections and political institutions, as well as issues of democratic stability, design, and transition.
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 | 0.000 | 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 | 0.000 | 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) | 0.005 | 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 it