Bibliographic record
Abstract
The introduction of Marxist thought in Iraq must be accredited to Ḥusain al-Raḥḥâl (1901–1981), who, though he never became a communist himself, was the first to introduce Marxist thought into intellectual circles in Baghdad. Al-Raḥḥâl was a high school student in Berlin in 1919 when the Spartacist uprising, an attempt by the Communist Party of Germany (KPD) to seize control of Berlin, took place; this event left a deep impression on him, and kindled his interest in socialism and Marxism. Returning to Iraq a year later, and profoundly affected by the unstable conditions of the country, under British occupation, he gradually started to teach Marxist and socialist thought. However, in his last days he expressed deep disappointment: With the seeds I have sown and worked so hard to intellectually nurture … I wanted to create an intellectual environment where scientific socialism would be the base of inquiry to understand our backward conditions, but we ended up somewhere else…. The impoverishment of Marxist thought today [1973] is much more alarming because it is much more regressive than it was fifty years earlier. Iraq Before the First World War The history of modern Iraq can be traced back to 1749 when the Ottoman Sultan appointed Sulimân Aghâ AbÛ-lailah, a Georgian Mamluk officer who was the governor of Basra (1749–1761), to the position of Wâlî (governor) of Baghdad. This appointment initiated the establishment of a semi-autonomous state in Iraq under Mamluk suzerainty.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".