Bibliographic record
Abstract
By analyzing six postcolonial African and Caribbean novels written by Léonora Miano, Tierno Monénembo, Marie-Célie Agnant, Henri Lopes, Simone Schwarz-Bart and Patrick Chamoiseau, this dissertation unravels the protean nature, operation, and socio-cultural implications of forgetting in connection with the representation of the historical phenomena of the past, key among which are the Middle Passage, Transatlantic Slave Trade and Colonialism. Critical attention is paid to how forgetting derives from discursive practices and subtly imposed political and insidious ideologies. As an inevitable force, forgetting is often construed as the obverse face of memory and consequently as a kind of amnesia or dysfunction. Breaking away from this postulation, my research demonstrates that forgetting is not just a denial of memory but a peculiar modality of processing traumatic historical experiences. Secondly, leaning on theorists such as Paul Ricœur, Édouard Glissant, Edward S. Casey, and Tzvetan Todorov, I argue that forgetting needs to be nuanced in the light of the exigencies of the moment and that, more than a mere contestation of History, frictions around it touch on issues of gender norms, identity politics, race, marginality, agency, and utopianism. Thirdly, I conclude that forgetting functions as a matrix of literary creativity and expression free from the reductionist schematic divisions that have impinged on the relationship between the colonized African and Caribbean and their Western counterparts. To be sure, this research deepens our insight into the workings of forgetting from a literary standpoint and helps us to grasp more clearly how the equilibrium between memory and forgetting is attained.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.020 | 0.029 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".