Bibliographic record
Abstract
The demonstrations, revolts, and protests collectively known as the Arab Spring have destabilized many long-standing autocratic governments in the Middle East. Central to this process were several types of information technology, including mobile phones, the internet, Twitter, YouTube, and Facebook. Unfortunately this issue is often represented in simplistic, technologically deterministic terms. This essay examines the distribution and growth of several digital information technologies in seven countries rocked by recent protests. It opens with a conceptual analysis grounded in the works of Jurgen Habermas, asserting that information technology has democratized the sphere of public debate throughout the Arab world. Second, it charts the Arab space of flows, the infrastructure and usage of the internet, cell phones, and social media. Third, it outlines government attempts to censor the Arab internet. The fourth part details how various information technologies were utilized by the Arab masses, particularly...
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".