Bibliographic record
Abstract
This article begins by discussing the rhetorical turn of the first sentence in M. T. Anderson's Thirsty. That first sentence reads: 'In the spring, there are vampires in the wind' (1997 p. 11). Do not these words sound similar to the subtitle of Tolkien's The Hobbit: 'There and Back Again'? I mean, doesn't the shape of the sentence that begins Thirsty remind us of the meaning of Tolkien's subtitle? The sentence begins with a prepositional phrase and ends with a prepositional phrase; in other words, it begins, with a phrase blowing in the wind and ends with the return of that wind; it begins, goes there, and then comes back, so to speak. When winter passes, a spring wind is sure to follow. If we are of a psychoanalytic cast of mind, we might say that rhetorically, the sentence enacts a return - the return of the repressed - but it does so slyly; it disguises the return of the repressed because we always have to disguise repressed content when it insists on emerging from the unconscious. Those pesky vampires insist on returning time and again; this time they come in with the wind - a sort of undead Chinook. My argument, then, is that fantasy rhetorically enacts the journey of return. When we begin a fantasy, we anticipate a return; we read retrospectively. Fantasy can deliver a productive nostalgia, a looking backward in order to look forward, fantasy opens a space for invention, and what returns in fantasy is both the repressed itself and the mechanism of repression.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.040 |
| Scholarly communication | 0.015 | 0.025 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.010 |
| 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".