Variables Relevant to Citizen Participatory Engagement in Technology-Mediated Democratic Systems
Bibliographic record
Abstract
Without citizen participation, democracy is empty of meaning. The purpose of this mixed-mode study is to identify variables relevant to citizen participation in advanced technology-mediated democratic systems such as Canada. A particular interest is to understand the comparative relevance of technological channels of communication, used by media, citizens and other social actors, to citizen participation. The results are based on primary data from 304 responses to a comprehensive survey and 20 in-depth interviews conducted by the author. Associations between 1048 questions about seven classes of participation and five groups of predictors are analyzed. In analysis, only non-parametric ordinal methods are used. First, outstanding predictors for particular forms and classes of participation are identified. Then, theoretical implications regarding predictors relevant to most classes of participation are formulated. Big data false discovery rate criterion is used to deal with the issues of high dimensionality and to identify outstanding relevances. A strong sense of social responsibility for fairness (nationally, internationally, and in international relations), national altruism, the feeling of being oppressed, attention to rights and freedoms, and political, economic, social, and cultural issues are associated with all types of citizen participation. Independent sources, empowered by the Internet and the World Wide Web, have outstanding relevance to citizen participation. Web 2.0 and other Internet based channels, such as telecommunications applications and mobile apps, have provided additional spheres of dialogue and expression for participating citizens. In this study, hundreds of other significant associations regarding particular forms of participation are identified and reported. They have implications for many social actors including the government, educational and media organizations, producers, policy makers, political parties, unions, activists, and parents.
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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 | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".