Party membership given up or reconsidered ?: Online political activism during the French presidential campaign 2012
Bibliographic record
Abstract
Abstract : Over the last 15 years, the academic literature has analysed forms of political activism the on-line environment might provide or facilitate. Empirical evidence brought information about online activists as people very interested in politics and over-active. At the same time, parties themselves were described as professionalizing, particularly with their communication activities. Membership is declining and members would progressively turn to be "supporters". However, the relationship between net-activists and party organizations hasn't been explored much: either surveys were conducted within parties, over-representing "traditional" party members and usually showing little difference between "offline" and "online" members; or they were conducted within the general population of voters, showing the limited impact of technologies over political engagement and political participation. This paper offers another perspective, looking at online political activism at an intermediary level between the general population and the party members. It explores how the (limited number) of people who get involved into an online campaign perceive parties and how they consider and practice activism. It shows that strong differences between party members and non-members remain, which tends to show that party boundaries haven't slackened yet, at least in France. However, qualitatively, distinctions appear between those who are mostly active online and those who are mostly active offline. The paper is based on quantitative and qualitative data (group and individual interviews) gathered during the French presidential campaign 2012, in the France-Québec project webinpolitics.com.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".