A Historical Study On Pandemics Spread in Modern Iraq: Their Economic and Social Effects, and Their Official, Popular, and Legal Treatments
Bibliographic record
Abstract
Health, economic and cultural backwardness was the dominant feature of the peoples of the ancient world, including Iraq in particular, where we read a lot about diseases and epidemics that ravaged the peoples of the world and killed millions of them, and we as Muslims also read about the plague that spread in the Levant at the beginning of the Islamic conquest of this Arab land and the expulsion of the Romans from it. And the Muslims lost many of them more than they sacrificed in the battles of the Islamic conquest, including the great companion Aba Ubaidah Amer Ibn al-Jarrah, the leader of the Muslims in the battles and then the governor of the Levant and Yazid Ibn Abi Sufyan, one of the leaders of the Islamic conquest. Between the sixteenth and the first half of the nineteenth century, modern Iraq witnessed more than (20) epidemic outbreaks, between limited and widespread. And between the period between the second half of the nineteenth century until the first quarter of the twentieth century, there were (19) epidemic outbreaks between wide and limited spread, especially the years 1867 to 1917 AD, and now after the outbreak of the Corona pandemic in our country and the whole world and its spread in Iraq at the beginning of the year 2020 AD, which infected Millions of the world’s peoples have collapsed in front of this pandemic, the best health services in the world, and it is still killing between day and night, in hot and cold weather, and all laboratories in the world are working to find an effective vaccine to stop this pandemic, which has brought the world to the brink of economic, health, educational, financial and social collapse.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".