Social Movements on the Internet: The Effect and Use of Cyberactivism in Turkish Armenian Reconciliation
Bibliographic record
Abstract
This article aims to explore the use of the Internet as a tool for political activism. Even though there are competing arguments about the virtues of online activism, it is important to demonstrate the use of the Internet for addressing political grievances. The Turkish Armenian reconciliation exemplifies one of the important aspects of the discussion on cyberactivism that is its ability to create public spheres. This paper argues that although the Internet is not as free and self-regulated as it is considered by cyber utopians, it still should be considered and explored further as a useful tool for social movements. Key words: Internet; Social Movements; Online political engagement; Censorship and SurveillanceResume: Cet article vise a explorer l'utilisation de l'Internet comme l’outil pour l'activisme politique. Quoiqu'il y ait des arguments de concurrence au sujet des vertus de l'activisme en ligne, il est important de demontrer l'utilisation de l'Internet pour adresser des reclamations politiques. La reconciliation armenienne turque exemplifie un des aspects importants de la discussion sur le cyberactivism qui est sa capacite de creer des domaines publics. Ce document argue du fait que bien que l'Internet ne soit pas aussi librement et autogere qu'il est considere par des utopistes de cyber, il devrait etre considere et encore explore plus plus loin comme outil utile pour les mouvements sociaux. Mots cles: Internet; Mouvements sociaux; Engagement politique en ligne; Censure et surveillance
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".