Digital Forms, Migrant Forms: Yaa Gyasi's Homegoing and Chimamanda Ngozi Adichie's Americanah
Bibliographic record
Abstract
My article argues that even though the novels, Homegoing by Yaa Gyasi and Americanah by Chimamanda Ngozi Adichie, are print texts, they construct their narratives through a reliance on digital modes such as hypertext, networked identities and elliptical sentence structures. Homegoing is constructed as a set of linked stories about characters who are dispersed across the world, and unaware of their blood lineages because of the rupture caused by the slave trade. Reading this novel can be much like scrolling through a hypertext, a genre that N. Katherine Hayles has described as a narrative that promotes “nonlinear, or more accurately, multilinear reading paths.” Hayles believes that it is usually electronic fiction that allows for such transformations within narratives but I argue that Homegoing's self-fashioning as an infinite network rather than a traditional print text illustrates that narrative transformation can also be observed in a print text that has been birthed in a contemporary media ecology. The aesthetics of fragmentation, ellipsis and dispersal express the elusive nature of national belonging and diasporic identity, a theme that is explored in even further detail in Adichie's Americanah wherein protagonist Ifemelu forces a connection between her many split subjectivities through the creation of an alternative self online. As the novel's longstanding relationship with frameworks of nation comes into contact with cyber-utopian, post-national natures of technology and digital media, Americanah becomes a site where networked identity alternatively interrupts, ruptures, and sometimes re-assembles national identity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".