“Love Rages”: Emotion, Agency, and the Superpositioning of Narrative in Tours of the Black Clock
Bibliographic record
Abstract
[Para. 1] "History, like all narratives, has a variety of possible outcomes. While feasible, their prediction is unlikely; we know too few of the variables and understand too little of how circumstances interact. What at first seems insignificant can cause catastrophe; human action is fundamentally erratic with potentially far-reaching and unforeseeable consequences. To process and assuage this profound uncertainty, we treat history as a story, and a postmodern view of history illuminates this instinct to narrativize events. Historicism claims that these narratives are essentially perspectives, based in their spatiotemporal context and lacking in objective truth. Still, at some point, we assume a particular narrative ends; World War II was devastating, Western history textbooks say, but finite. While the war’s effects reverberate forward in time, we latently accept that the narrative of the war, proper, is contained within temporal parameters: 1939 to 1945. That is, once Japan officially surrendered in September 1945, the war ended. Steve Erickson, in his 1989 novel Tours of the Black Clock, shatters this assumption."
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".