The Gender Question and the Involvement of Women in Pre-Colonial Igbo Warfare in Equiano’s Interesting Narratives
Bibliographic record
Abstract
On the 2nd of November 2018, an unusual gathering took place at the Theatre Hall of the Faculty of Arts at the University of Nigeria in Nsukka where Paul Lovejoy, a Professor of History at York University in Canada, was hosted as the guest lecturer. His lecture dwelt on Gustavus Vassa (Olaudah Equiano) and the Trans-Atlantic Slave Trade: Representation, Identity and Reality. The curiosity of faculty members and students at the University of Nigeria, Nsukka around the thought process of this leading Africanist Historian made for a very fruitful event. The various debates raised by the iconoclastic scholar tampered with my sense of judgment as the convener; thus, I was convinced to re-evaluate Equiano’s narratives, particularly focusing on its gender dimension as well as its exploration of women’s involvement in pre-colonial Igbo warfare. This paper examines the views of academics on Equiano's narratives on warfare, especially Equiano’s various enigmatic assumptions he raises. In lieu of this, the thesis of this paper is that contemporary Igbo studies have a lot to gain from Equiano’s narratives in the reconstruction of the historiography of pre-colonial Igbo warfare, especially regarding the neglected role that women have played, as this is a fact not readily accepted by many professional Igbo historians. Furthermore, using Equiano’s narratives, this paper concludes that women were relegated in traditional Igbo settings, and the claim that Igbo society was democratic and republican was over exaggerated by nationalist historians.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.027 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".