Political outcomes of digital conversations : case study of the Facebook group "Canadians against proroguing parliament"
Bibliographic record
Abstract
Since the emergence of the Internet, scholars have had mixed opinions regarding its role in influencing levels of political participation. Two frameworks, the mobilization and the reinforcement theses, were created from these opposing views. The introduction of social networking websites (such as Facebook) offers new platforms with which to test these opposing theories on. This study investigates the Facebook group ―Canadian‘s against Proroguing Parliament,‖ to determine: 1) what the members' motivations were for participating in the group, 2) whether the group attracted formerly marginalized voices to participate on the group, or simply reinforced those who were already active in the political process, and 3) whether the participation of members on the group translated into offline or real world political participation. The findings suggest that the group‘s members had a variety of reasons for joining the group. As well, the findings suggest that the group both mobilized reinforced its participants. Finally, the data indicates that in some instances, the group‘s members translated their online participation into real world political activity.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".