Anatomy of Denial: Manipulating Sources and Manufacturing a Rebellion
Bibliographic record
Abstract
Turkey’s and Sudan’s governments use similar genocide denial tactics. This article, by closely examining Turkey’s tactic of claiming an Armenian rebellion, can help scholars combat similar claims by Sudan. Deniers claim the Armenian Revolutionary Federation (ARF) fomented a rebellion, but they elide the fact that Turkey’s ruling party tried to recruit the ARF to form a fifth column behind Russian lines. They also dismiss as a subterfuge the ARF World Congress decision that Ottoman and Russian Armenians must join their respective armies. These authors ignore multiple sources describing the interparty negotiations but base their positions on a book by Esat Uras, a perpetrator of the genocide, which created the template for denial. Deniers also distort the formation of volunteer regiments in the Russian army, made up predominantly of Russian Armenians, into a mass movement of Armenians deserting the Ottoman army to conduct guerilla warfare. The evidence for these false claims consists of a single Ottoman intelligence report and distortions of Armenian sources. But the internal deliberations of the ARF show no evidence of a conspiracy with Russia.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".