Comparing Civic participation Between Korea and Canada
Bibliographic record
Abstract
This research examines the difference in civic participation between Korean and Canadian citizens in two categories – social engagement (participation in general social groups) and political activity by using the Korea Social Integration Survey (SIS) and the Canadian General Social Survey (GSS). According to the results of this study, Canadians show higher social engagement than Koreans, while Koreans exhibit higher political activity, showing higher combined civic participation between individual citizens. This heightened civic participation by Koreans also reflects a stronger sense of collectivism. The results of the analysis on the effect of civic participation for each country show that, in Korea, both trust and sense of belonging were positively associated while in Canada, trust was negatively associated, and sense of belonging more positively associated than in Korea. The difference between the two countries can be attributed to the negative association found in institutional confidence as well. In Canada, active participation in politics implies that civic participation is part of more forward-looking action that shows greater individual preference and intention in comparison to civic participation of Korean citizens influenced more by collectivism. As such, this research implies that Korea needs to enhance individual civic identity in order to overcome collectivism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".