Populating the Novel: Literary Form and the Politics of Surplus Life by Emily Steinlight
Bibliographic record
Abstract
Reviewed by: Populating the Novel: Literary Form and the Politics of Surplus Life by Emily Steinlight Daniel Stuart Populating the Novel: Literary Form and the Politics of Surplus Life by Emily Steinlight; pp. 223. Cornell UP, 2018. $68.05 cloth. Exploring the relationship between population dynamics and nineteenth-century literature, Emily Steinlight’s Populating the Novel: Literary Form and the Politics of Surplus Life (2018) compels us to think about life in the aggregate amid the crowded social worlds of emerging modernity. In a period recognized for classical liberalism and subjective orientations, Stein-light reads the nineteenth-century novel as emphasizing human beings en masse—especially as swelling populations made individual lives more redundant. Such a “surplus of humanity,” in Malthusian terms, “unexpectedly became an enabling condition for literary narrative” (3) as novels from Mary Shelley’s The Last Man (1826) to Thomas Hardy’s Jude the Obscure (1895) not only highlighted demographic excess but foregrounded the political patterns developing alongside it. This “biopolitical imagination” oversaw the conflicts embedded in urbanized masses and created new implications [End Page 153] for the value of human life, as older contractual models of society could no longer be observed. Such a perspective not only reconsiders the pejorative connotations of population management but re-examines the novel’s intentionality, one that critics from Ian Watt to D.A. Miller have seen as trying to “produce a stable, centered subject in a stable, centered world” (Miller xi). Steinlight’s ideas on “biopower” and “biopolitics” stem from Michel Foucault’s transformative accounts of a society resituated near the end of the eighteenth century. And much of her argument engages certain nuanced approaches to New Historicist criticism. The emergence of the biological sciences, for example, was deeply embedded in the evolving political and economic models, through which quantifiable analysis could be used to gauge population outcomes. If human groups, like groups of other organisms, could be observed and controlled through scientific means, then the governance of populations could be conceived of in ways that demanded similar modes of nurture and restriction. Like Frankenstein’s monster, whom the author likens to “an avatar of the multitude of which it is composed” (45), the need to optimize the masses’ potential also meant limiting their power. Early nineteenth-century novels such as those of Shelley and Thomas De Quincey’s Confessions of an English Opium Eater (1821) highlight this view by focusing on the need to regulate populations and their animalistic “human turmoil” (2). Yet Steinlight is quick to point out how such an emphasis also helped solidify the genre. Embodying the existing social framework gave “unexpected life to form” in the context of the novel, which found its formal vitality in the “excessiveness of species life” (28). In the shadow of a revolutionary age, biopolitics found a home in novels concerned with a population’s potential. But Steinlight sees the Victorian era as introducing crucial aspects of life in the aggregate, especially where urbanizing trends helped foreground the novel’s concern with politics and human contingency. Her reading of Mary Barton (1848) combines the ideas of Karl Marx, Friedrich Engels, and Henry Mayhew to perceive how quantitative population analysis inevitably created redundancy within human experience. Such “demographic remaindering” of figures marginalized and destroyed due to population excess formed the crux of industrial novels as much as it did for more mainstream narratives (21). The profusion of characters throughout works by Charles Dickens is no secret, but Steinlight observes how his “strategic overcrowding of narrative space necessarily alters literature at the level of form” (11). For all his aversion to Malthusian utilitarianism, Dickens is ironically reliant on surplus populations. Instead of the collective mass accommodating the individual subject, works like Bleak House (1853) and Hard Times (1854) depend on the fatal attrition of certain characters to achieve their aims. This idea further resonates in the naturalism of Hardy, in which expendable characters and “the specter of failed development” prove to be an “underlying condition of the genre” (169). Like the epithetical Little Father Time in Jude the Obscure, whose name foregrounds the [End Page 154] fate of supernumeraries in nineteenth-century fiction, the stability and sustainability of individual lives...
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".