Capital Distress: Productive Citizenship and Mental Health in Adolescent Literature
Bibliographic record
Abstract
This dissertation explores the complexities of adolescent mental health under neoliberal capitalism in twentieth- and twenty-first-century U.S. fiction about and for adolescents. Drawn on research that defines youth citizenship as responsibilities-based in nature, this project outlines the ways contemporary young adult (YA) novels of mental distress reveal an inextricable link between adolescent mental health and the conditions of what I term productive citizenship. Constituting my theorization of productive citizenship are three distinct tenets adolescents must adhere to: (1) displaying the motivation to achieve specific goals; (2) showing a propensity for self-reliance and individuality; and (3) accepting the translation of political concerns into personal, psychological issues and resolving those issues through individual treatments. Should an adolescent refuse or be unable to uphold any of these tenets, they become a risk to society and must be tamed. I contend that contemporary YA novels of mental distress detail this taming process. My introduction reviews the relevant research to this discussion, which includes but is not limited to Marxist and Youth criticism, as well as contemporary YA scholarship. Chapter one considers how the history of productive citizenship threads together with the literary roots of adolescent mental distress in novels by J.D. Salinger, Joanne Greenberg, John Neufeld, and Virginia Hamilton. In Chapter two, I interpret therapeutic treatment as a contemporary disciplinary practice of femininity in novels by Julie Halpern, Laurie Halse Anderson, and Meg Haston, while in chapter three I examine how masculine silence informs adolescent mental health in novels by Stephen Chobksy, Michael Thomas Ford, and Adib Khorram. Lastly, chapter four explores the use of psychiatric spaces in novels by Ned Vizzini and Francisco X. Stork to argue how the depiction of these facilities undermines the neoliberal definitions of “health” by replicating the living conditions of a pre-industrial society. Collectively, these novels inevitably urge the acceptance of broader political concerns as individual issues by centring the symptoms of distress rather than its root causes. As a result, the model of young adulthood encouraged within the neoliberal capitalism of many recent YA novels of mental distress is productive citizenship.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".