Le mode de scrutin a-t-il un impact sur le processus de décision électorale et cet impact varie-t-il en fonction de la sophistication politique ?
Bibliographic record
Abstract
Do electoral systems have an impact on the vote determinants and does that impact depend on political sophistication?Studies have not answered that question in a satisfying way and have flot considered the electorate heterogeneity but have shown that electoral systems impact the number of parties, their objectives and their campaign strategies.We have tested three hypotheses.First, the weight of party identification should vaty depending on the electoral system, mostly amongst less sophisticated people.Secondly, issues should matter more under proportiona] systems and that variation should be greater amongst the less sophisticated.Lastly, leaders should matter more under majoritarian systems and that effect should be greater amongst the less sophisticated.Our quantitative analyses rely on regular logistic regressions and use the Comparative Study of Etectorat Systems data.We show that electoral systems do have a systematic impact on vote choice determinants: party identification and leaders matter more under majoritarian systems and issues matter more under proportional systems.However, the effect of electoral systems on vote determinants is not systematically stronger amongst the less politically sophisticated people.
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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 | 0.017 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.003 |
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".