Working it Through: Trauma and Autobiography in Phoebe Gloeckner’s A Child’s Life and The Diary of a Teenage Girl
Bibliographic record
Abstract
This article explores the relationship between autobiography, trauma, and comics in the work of Phoebe Gloeckner, and demonstrates through close readings how the visual and fragmented comics form can be mobilized both for therapeutic purposes and as a means to assert agency for a victim of trauma. Comics autobiography, crucially, externalize the self as a drawn visual representation on the page that is self-evidently other to the contractual author. This splitting of the subject into a narrating author and a narrated visual representation on the comics page is congenial to the representation of traumatic memories, which theorists have long recognized to be manifesting themselves as the intrusion of visual snapshots into normal consciousness. The comics form, further, functions as a kind of visual scriptotherapy, which allows the author to dissociate the traumatic memory onto the page and create a narrative from a series of disjointed memories. Readings of selected passages from Gloeckner’s two books A Child’s Life and The Diary of a Teenage Girl illustrate how her use of the comics form take advantage of its inherent ability to present traumatic memory and construct a literal eyewitness in the reader. Finally, the article argues that the form’s ability to establish narrative from fragmented, repetitious, and disjointed images allows Gloeckner to organize painful memories into a coherent sense of self, and in this way work through her trauma.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".