Bibliographic record
Abstract
What is the nature of mind control? Does it exist? Sure, mind-altering drugs and hypnosis offer limited types of this control, but could media play a similar role? What role does media play in the structuring of our consciousness? This novella follows a consciousness that has become unmoored and loops through the world, its experience shaped by the media it previously had consumed and enjoyed. The main character, Lionel Grene, finds himself unable to escape the plot of a paranoid espionage novel that he has created. Set in mid-1990s Ontario, Lionel struggles to comprehend his situation, spiralling through the experience of the conspiracy filled plot of his spy novel. This plot is based in the true World War II history of Durham Region, Ontario. Places like Camp-X, Defence Industries Limited, and Camp 30 were real places. However, in Grene’s conditioned imagination, they become dens of plotting and manipulation. Then again, this might be historical fact too. Drawing on the novels of Thomas Pynchon as inspiration, a key aspect of this project is Grene’s slipping from fabulation (writing a novel) into confabulation (a memory error causing him to take himself as the protagonist of that novel). But beyond that, the project also interrogates the idea of media as subconscious programming.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.154 | 0.038 |
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".