Bibliographic record
Abstract
Dissenting votes in parliamentary systems are overt displays of defiance by individual Members of Parliament (MPs) vis-à-vis their parties. Dissension is particularly surprising as in the vast majority of situations voting against one's party yields no change in legislative outcomes while still generating costs for MPs. This study examines the decisions of elected representatives who face conflicting incentives. A model is developed where MPs choose to dissent in an effort to build reputations with their local constituents. Using all 32,216 observations at MP-bill-vote level for the 39th Parliament of Canada, a reputation building hypothesis is specified and tested. I provide evidence that MPs whose previous election was competitive are 13 percent more likely to cast any dissenting vote and, for a one standard deviation decrease in expected margin of victory, 2.3 percent more likely to defect on any given vote, results which suggest that MPs are actively attempting to build reputations with their local constituents. / Les voix dissidentes dans les systèmes parlementaires sont une manifestation ouverte de défi par des députés vis-à-vis de leurs partis. La dissension est particulièrement surprenante, car dans la grande majorité des situations, ayant voté contre son parti ne donne pas de changement dans les résultats législatifs, mais génère des coûts pour les députés. Cette étude examine les décisions des élus qui font face à des incitations contradictoires. Un modèle est développé où les députés choisissent de différer afin de construire une réputation avec leurs électeurs locaux. En utilisant tous les 32 216 observations au niveau député-projet de loi-vote pour la 39e législature du Canada, une hypothèse de construction de la réputation est spécifiée et testée. Je fournis la preuve que les députés dont l'élection précédente était compétitive sont 13 pour cent plus susceptibles de différer et, pour une diminution de l'écart d'une norme de la marge attendue de la victoire, de 2,3 pour cent plus susceptibles de faire défection à tout vote donné, des résultats qui suggèrent que les députés tentent activement de construire des réputations avec leurs électeurs locaux.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".