Does Civic Education Foster Civic Duty? A Systematic Cross-Country Analysis of the Effect of Three Forms of Civic Education on the Sense of Civic Duty to Vote
Bibliographic record
Abstract
Abstract This article investigates if civic education can spur a sense of duty to vote and, in this way, help to augment the number of voters and diminish inequality in participation. I perform a systematic cross-country analysis of the link between different forms of civic education and civic duty, using the data from the 2016 International Civic and Citizenship Education Study (ICCS) that include 23 countries. The results show that three key civic education mechanisms—civics courses, active learning strategies and open classroom environment—exert an influence on civic duty but that civics courses have the strongest effect. Country-level analyses confirm that civics courses are more influential on civic duty than the other types of civic education. This evidence elucidates which channels of school socialization may help to develop a sense of duty in adolescents, as well as the relative effect of each mechanism.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".