Bibliographic record
Abstract
Voter lors d’une élection fait-il l’objet d’un devoir moral ? Les raisons philosophiques susceptibles de justifier l’existence d’un devoir de vote demeurent largement tenues pour acquises dans les débats publics, malgré la popularité de cette croyance et son utilisation pour condamner publiquement l’abstention. Cette situation paraît difficilement tenable dans un contexte de malaise démocratique ambiant, où les citoyens semblent de plus en plus nombreux à douter de leur propre démocratie. Heureusement, la littérature portant sur l’éthique du vote a connu un important essor de travaux examinant l’idée d’un devoir de vote, donnant lieu à une pluralité d’arguments en faveur de cette thèse ainsi qu’à son lot d’objections. Cet article vise à faire le bilan de ces débats, à souligner les principaux points de désaccord qui opposent les différents intervenants et à tirer les principales leçons pour le renouvellement des attitudes des citoyens à l’égard des démocraties contemporaines.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".