Entangled states: Putting affect theory into play with John Burnside’s A Summer of Drowning
Bibliographic record
Abstract
Abstract This article reads John Burnside’s A Summer of Drowning (2011) as resistance to the progress narratives or ‘man-making tales’ (Haraway 2016) that threaten life in fiction and in reality. The choice in Burnside’s gothic narrative and in affect theory is not to drown or not to drown but how to engage with old habits of thought that drown us in recursivity. The Norwegian island Kvaløya/Sállir is both marked and obscured by troubling events in history and in fiction, though it is impossible to tell which is which. At 28, narrator Liv Rossdal reflects on the disturbing events of midnattsol when she was 18. In the temporal distortions, it is hard to know what actually happens, but Liv and her artist mother Angelika survive by cultivating different styles of noticing their entangled states and ecologies (Tsing 2015, Barad 2007). Noticing the ways that ‘real’ characters are entangled with fairytale characters like Narcissus and the huldra disrupts habits that centre anthropocentric points of view, that eclipse other ways of making history, and that commoditize certain types of desire. Liv and her mother resist the simplifications, linearizations, and commoditizations of man-making habits by cultivating ‘unnatural’ connections. What else can bodies do, besides drown in representational thought in these disturbing times?
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".