« White Writing », « Dark Continent » : les enjeux de la représentation du paysage dans la littérature sud-africaine
Bibliographic record
Abstract
Les enjeux de la représentation d’un paysage que l’on voudrait national sont cruciaux quand la nation, la « communauté imaginée » de Benedict Anderson, se cherche encore, comme en Afrique du Sud après l’apartheid. La transition n’est pas que politique ou institutionnelle : c’est toute une culture qu’il faut modifier, qu’il s’agisse d’un hymne national auquel toute la « nation arc-en-ciel » s’identifie, ou de portraits du pays dessinés par les écrivains. Cet article rappelle donc les enjeux de cette question et dresse un panorama du paysage sud-africain dans la littérature du pays, en en repérant les topoï et la manière dont les auteurs noirs, blancs ou métis interrogent les modes de représentation picturale du pays et les traditions littéraires qui leur sont associées.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".