Bibliographic record
Abstract
Cloud Theory presents a critical, intimate study of post-MeToo masculinity in the form of a novel. Dr. Eli Sabaktani, professor of Speculative History and Myth at Osiris University, finds the diary of Johnny Gray, one of his graduate students, who has recently been called a “known abuser” online. Seeking to understand and redress harm, Eli publishes the diary, not without first gracing its pages with an impassioned preface and copious annotations that flesh out the story’s historical, mythological, and philosophical underpinnings while revealing Eli’s own gender trouble. Johnny’s diary tells the story of a group of friends who attempt to operate a queer-feminist community space in Montréal. Johnny questions his own position and authority within the group, elaborating a “cloud theory” that would replace the rigid impassivity of normative masculinity with a more fluid and cloud-like vulnerability. How might we loosen or “liquefy” the subjective, political, and economic categories that bind, limit, and oppress us, without completely undoing the psychic and social boundaries that nourish and protect us? How to create a safe space that is yet still porous? Johnny attempts to put his ideas into practice, but tensions rise as the group navigates the ensuing COVID pandemic, the protests following the murder of George Floyd, and finally the callout leveled against Johnny that derails the project and sends him into a crisis. Johnny finds momentary reprieve in email exchanges with Eli where they discuss masculinity, shame, power, and perfection, until Eli’s lectures drive him to seek a more pragmatic and compassionate resolution to his story. Cloud Theory seeks to understand the workings of structural power, how it seeps into the body and pries open even our most intimate relationships. Storytelling as methodology allows for a more agile mapping of these liquid dynamics, inflected as they are by personal histories fraught with trauma and shame. In the contested cracks between identity, affect, and power, Cloud Theory attempts to rethink what a male body is, what it can do, and what it might become.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.066 | 0.013 |
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".