Bibliographic record
Abstract
This article traces the influence of the Arab Spring on Iraq as activists staged fervent protests against the corruption, sectarianism, and favoritism of Nouri Maliki's government. A group of young Iraqi intellectuals, journalists, students, government employees, and unemployed youth posted their plan to organize demonstrations against the government using social media in February 2011. This study investigates the use of Facebook and YouTube, which bypassed the government's attempt to limit the coverage of these protests. Indeed, the events during the Arab Spring in Iraq crossed sectarian lines and united Iraqis against the Shiite-dominated government. I examine the five most popular Facebook pages and more than 806 YouTube clips and their 2,839 comments related to the Iraqi Arab Spring. The study reveals that young Iraqi men between the ages of 25 and 30 were the most active bloggers, while those between the ages of 20 and 24 were the most active commentators during the protests. Iraqis living in the United States and Canada played an important role by posting YouTube clips and comments. A gender disparity was evident; Iraqi men posted more video clips and comments than women.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".