Subjectification and Confession in Contemporary Memoirs of Abduction and Prolonged Captivity
Bibliographic record
Abstract
A striking trend is emerging in the Canadian and American literary landscape, and memoirs with the following narrative trajectory are now widely read: a stranger abducts a young woman, and holds her captive for years. She endures sexual, physical, and emotional abuse, eventually escapes, and returns to her former life. The sole scholarly discussion about these memoirs frames them as empowering for the authors, but the social and economic factors that inform these texts remain unaddressed. Drawing from Michel Foucault's discussion of the confession, this article complicates and extends this analysis. First, it situates memoirs by Elizabeth Smart, Amanda Berry and Gena DeJesus, Jaycee Dugard, Michelle Knight, and Josefina Rivera as examples of the Foucauldian sexual confession. It then maps the ways memoirs enable the authors to voice their understanding of the social and economic factors that both gave rise to their plight and inform media discussions that blame them for their suffering. I will ultimately argue that memoirs function as a public venue to resist or reject dominant interpretive frames that shape a survivor's experiences, while simultaneously reaffirming the ubiquity of these lines of thinking.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.026 | 0.065 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".