Bibliographic record
Abstract
The significance of gender to depictions of the nation is a significant discussion within African fiction. Guinea-Bissau, however, has been somewhat neglected. This thesis will re-dress this imbalance by juxtaposing Abdulai Sila’s Mistida trilogy with fiction by Filomena Embaló, Domingas Samy and Odete Semedo. It considers the symbolic representations of women in Sila’s work, where he writes the colonised nation upon the female body, and attempts to create women’s agency by inscribing them with future power. However he simultaneously eradicates their historical importance. I explore the narratives of female-authored fiction and argue that whilst there is a tendency to write about inequality in the domestic space, women are equally concerned with discussing national identity and experience through the prism of the intimate. I revisit Sila to examine the significance of masculinities to his narration of the nation. He repeatedly complicates the image of a national hero in texts that connect Guinea-Bissau to global black masculinities and inscribe the crises of the post-independence nation upon the male body. Insofar as the literary imaginary contributes to the construction of nationhood in Guinea-Bissau, this thesis demonstrates that the negotiation of gender symbolism and power relations are intrinsic to this process in fiction.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".