Into the Heart of Darkness: Cosmopolitanism vs. Realism and the Democratic Republic of Congo
Bibliographic record
Abstract
It was 42 years before the end of World War II that Joseph Conrad wrote his infamous novel "Heart of Darkness," yet today its relevance to the Congo remains starkly the same, as the aegis of colonialism has left a devastating footprint. The novel explores the hypocrisy of Belgium's imperialism as the act of civilizing the African became quite uncivil. The imperial incivility, political factionalization, and decades of authoritarian rule and war have led the United Nations (UN) to enter the Congo, quite like Marlow's travel up the Congo River. Yet, amidst the chaos of Belgium's enterprise and the aftermath of World War II, the Congo offers a troubling and difficult case for policymakers and for international relations theory. This paper aims at pondering this case to hopefully shed light into the heart of darkness and give an explanation for 'the horror' that Kurtz only realized at his final moment. \nFollowing World War II, it was abundantly clear through international consensus that the urgency for preventive action against another world war required the reorganization of the League of Nations system. The former colonial and imperial powers of Europe were decimated and the United States and Russia stood as victors against an impetuous regime. The global order was changing rapidly with the creation of the atomic bomb and the rise of the United States and Russia as superpowers. [Full text of abstract available in document.]
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".