Bibliographic record
Abstract
This Element endeavors to enrich and broaden Southeast Asian research by exploring the intricate interplay between social media and politics. Employing an interdisciplinary approach and grounded in extensive longitudinal research, the study uncovers nuanced political implications, highlighting the platform's dual role in both fostering grassroots activism and enabling autocratic practices of algorithmic politics, notably in electoral politics. It underscores social media's alignment with communicative capitalism, where algorithmic marketing culture overshadows public discourse, and perpetuates affective binary mobilization that benefits both progressive and regressive grassroots activism. It can facilitate oppositional forces but is susceptible to authoritarian capture. The rise of algorithmic politics also exacerbates polarization through algorithmic enclaves and escalates disinformation, furthering autocraticizing trends. Beyond Southeast Asia, the Element provides analytical and conceptual frameworks to comprehend the mutual algorithmic/political dynamics amidst the contestation between progressive forces and the autocratic shaping of technological platforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".