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Record W2158739584 · doi:10.5539/ells.v5n1p13

Historicizing Joseph Conrad's Heart of Darkness: A Critique of King Leopold II’s Colonial Rule

2015· article· en· W2158739584 on OpenAlexvenueno aff
Isam M Shihada

Bibliographic record

VenueEnglish Language and Literature Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicJoseph Conrad and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismPretextGenocideCivilizationState (computer science)Free stateColonial ruleHistoryArtAncient historyLawPolitical sciencePolitics

Abstract

fetched live from OpenAlex

This study examines how Conrad's Heart of Darkness has played an important role in exposing the brutal reality of Belgian colonialism in the Congo Free State under the pretense of a civilizing mission. The study focuses on how Conrad’s Heart of Darkness has been instrumental in revealing the atrocities committed by King Leopold II’s agents in their desperate scramble for the rich resources of the Congo, such as ivory and rubber. King Leopold II’s atrocities may account for the death of almost ten million Congolese natives, a crime of a genocidal scale, which has terribly affected the people of the Congo to this day. Conrad renders his own anti-colonial critique through his central character, Charles Marlow, who learns about the brutal methods of Belgian colonialism while on a journey to the Congo searching for the infamous ivory agent, Kurtz. The study examines how Conrad's Heart of Darkness critiqued King Leopold II's colonial rule and contributed to the launching of an international protest which exposed and put an end to the genocide committed against the Congolese in the name of civilization, science, and progress. The campaign eventually forced King Leopold II to quit the Congo Free State in 1908, and unraveled one of the most heinous crimes in history committed under the pretext of “civilization”.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.268
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

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