Bibliographic record
Abstract
If, as Roberto González Echevarría argues, all fiction is written in relation to the archive, African literature is written with an eye to the colonial archive. That archive reflected an imperial will to knowledge and was an information system collected in an attempt to define and so control Africans. Writers such as Achebe, Tutuola, La Guma, and Coetzee have imagined it as a prison, as hell, or as a great maw. The meaning of the colonial archive changed as it receded into the past. African writers seek to supplement the archive in order to correct it (Sleigh, Gappah, D. Diop); resurrect those suffocated in it (Achebe, Christiansë); find ancestors (Krog, Joubert); escape the archive’s surveillance by imagining an outside (Brink, Coetzee, Gordimer); or honor the dead (Samkange, Djebar). African literature resists and subverts the archive but is also haunted by it. The colonial archive is itself now a trope shared among African writers (Achebe and Adichie), becoming an element in the archive of African literature.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.009 |
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".