Economies of Reputation: Jonathan Franzen’s Purity and Practices of Disclosure in the Information Age
Bibliographic record
Abstract
A central project of Jonathan Franzen’s Purity (2015) is the attempt to situate the development of the Internet and of technocratic corporations within the historical context of Marxist efforts in the postwar era. There remains a dearth of critical work on Franzen’s Marxist interests, and he retains a reputation of literary conservatism, though Purity shares with other Franzen novels, like The Corrections (2001), an interest in the possible directions that remain for leftist ambition in the aftermath of failed radical projects and in modes of collective action that would account for the practical limitations of a neoliberal age. Following what one character refers to as the “mania for secrecy” that characterizes digital media in the era of Wikileaks, Purity has at its center the relation of the human user’s social ties to a medium dominated by corporate giants and by new measures of governmental surveillance. Franzen’s novel is suspicious about the possibility that there are ways of interacting with digital media that can minimize the ideological effects on human relationships, with various subplots of the novel emphasizing the power of a technocratic Internet to manufacture and revoke perceptions of an individual or cause’s ideological purity, as secrets can be indefinitely stored and achieve viral status with immediacy upon reveal. Acts of confession and the voluntary disclosure of traumatic and criminal histories are thus given a privileged status in Purity, with the novel suggesting that the establishment of any collectivist projects necessitates transparency, but must resist the urge promoted by contemporary Internet culture to fetishize such exposure or assume its inherent radicalism.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.040 |
| Scholarly communication | 0.025 | 0.023 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".