Social Capital, Internet Connectedness Political Participation: A Four-Country Study
Bibliographic record
Abstract
This paper examines the relationship between social capital, Internet connectedness and political participation in Australia, Canada, the United Kingdom and the United States. While a number of studies have hypothesized a relationship between social capital and political participation, few have been able to model, measure and compare levels of engagement beyond the general consensus that higher levels of social capital mean higher levels of political involvement. While some studies have claimed that Internet use has negative effects on these areas of life, others have argued for negligible or even positive outcomes. We develop a typology of Internet users (socialisers, utilitarians, and game-players) and explore a relationship between technological connectedness and political participation that we hypothesize is positively moderated by social capital connectedness. Using structural equation modeling on the Survey2000 dataset, we find no significant negative effect of connectedness on social capital, a negative effect of connectedness on political participation in the United States except when mediated by social capital, and different degrees of positive effects of connectedness on social capital and political participation varying by Internet user and by country.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".