The Troubled Encounter Between Postcolonialism and African History1
Bibliographic record
Abstract
This paper examines the complex engagements between what it calls the “posts” – poststructuralism, postmodernism and postcolonialism – and African studies. Specifically, it analyzes the analytical connections and contestations between postcolonial theory and African historiography. The paper interrogates some of the key ideas and preoccupations of both postcolonialism and historiography and explores the intersections between them. It is argued that the ambivalence and sometimes antagonism to postcolonialism by many African scholars is largely driven by ideological and ethical imperatives, while the troubled encounter between African history and postcolonialism is rooted in apparent intellectual and epistemic incongruities. Linking the two is the powerful hold of what I call nationalist humanism in the African imaginary, the nationalist preoccupations of African intellectuals, and the nationalist proclivities of African historiography. Productive engagement between African history and postcolonialism is of course possible, but it requires mutual accommodation, the incorporation in postcolonial studies of the insights developed in African historiography, and within the latter of some of the constructive interventions of postcolonial theory. Ultimately, however, I believe postcolonialism has serious limits in its methodological and conceptual capacities to advance what I would call the historic agendas of African historiography.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.041 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".