Home Sweet Home: Exil, déracinement et retour aux sources dans October de Zoë Wicomb
Bibliographic record
Abstract
Zoë Wicomb was born in Namaqualand, South African but has lived in Britain, then in Scotland since the 1970s. Her latest novel, October, as much as her previous literary works, deals with the legacies of apartheid. It also explores themes of family secrets, race, immigration, and homecoming. Therefore, the present article tasks itself with analyzing Wicomb’s South African protagonist Mercia Murray’s return to the roots, her native land Kliprand, showing first her condition of expatriate in Glasgow and the perspective from “the Elsewhere” she has for Africa. Then, the second part is devoted to her unhoming, unbelonging, and estrangement from her family and community inasmuch as she is constantly confronted to the following question: Where does anyone belong? Finally, the last part focuses on Mercia’s complicated family legacy and the hidden secrets that seem to haunt her, considering her position as “Coloured” or mixed-race South African. Née à Namaqualand, en Afrique du Sud, la romancière Zoë Wicomb a longtemps vécu en Angleterre, puis en Écosse. A l’instar de ses précédents romans et nouvelles, son dernier roman, October, traite de l’apartheid et de ses séquelles au sein de la société sud-africaine. Il explore également des thèmes liés aux secrets de familles, au racisme, à l’émigration et au retour au pays natal. Cet article analyse l’amer retour aux sources de Mercia Murray, la protagoniste sud-africaine, à Kliprand en présentant dans un premier temps sa condition d’expatriée à Glasgow et le regard qu’elle porte sur l’Afrique depuis “l’Ailleurs”. La deuxième partie est consacrée à son expérience d’aliénation et de déracinement dans la mesure où elle est confrontée à la très complexe question d’appartenance, se demandant constamment à quel territoire elle appartient réellement. En fin, il s’agit de se pencher sur les secrets de famille qui semblent hanter le personnage de Mercia, tout en considérant sa position de métis sud-africaine, ou “Coloured” dans une Afrique du Sud postapartheid.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".