Bibliographic record
Abstract
WAY SHE GOES – ABSTRACT \n \nSet in the present day in west-end Toronto and a few small towns in Southern Ontario, Way She Goes is a novel of love and care, music and memory. The two principal characters are Cisco Wakely and his nana, Dorothy. Cisco’s parents are absent so grandmother and grandson have been together for the almost eighteen years of Cisco’s life. \nUntil recently, Dorothy was the mainstay of the household, providing a slightly shaky foundation for Cisco’s dream of musical success, fueled in part by her experience as a groupie in the 1970s. Lately, things have become tricky because Dorothy is losing it. The novel opens with a visit to the doctor which results in a diagnosis of early-onset dementia. Cisco, who has been helping with the finances for a while, has to balance obligations to his nana, the landlord, and his band. He writes final high-school exams, sells enough drugs to pay the rent, moves Dorothy to an assisted care facility, and prepares to go on tour. But as he is loading his drums into the band’s van, she arrives with bruises and horror stories. There’s no time to spare. Their first gig is that night. Cisco has no support, doesn’t want to return Nana to the possibly abusive facility, can’t think what to do except to take her on tour with him. \nOver the next few days, Cisco learns about love and trouble. He hooks up with his lead singer, finding passion and jealousy inside himself. The band appears headed for success, until Cisco is threatened by rival drug dealers, and discovers his nana’s most closely-guarded secret. \nAll this sounds pretty grim, but the novel is primarily comic. Cisco’s best friend is boundaryless, impossible to predict. His other band-mate is a part-time mermaid. Cisco himself is foul-mouthed, angry but optimistic, checking in with a God he simultaneously believes in, doubts, and makes fun of.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".