Book Review of Wong, Lindsey. (2018). The Woo-Woo: How I Survived Ice Hockey, Drug Raids, Demons, and my Crazy Chinese Family. Vancouver: Arsenal Pulp Press.
Bibliographic record
Abstract
Lindsay Wong's book, "The Woo-Woo" is a coming-of-age memoir that uses dark and satirical humour to illustrate her dangerously bizarre upbringing in her Chinese immigrant household.In her recollections, Lindsay presents various critical aspects of her life that all include the Woo-Woo.The Woo-Woo's existence and the stories associated with it cause most to differentiate their childhoods from that of the author, leading to emotions such as dejection and pity.Her borderline abusive childhood and the resulting trauma lead Lindsay to reflect on her family's personality.Altogether, Lindsay narrates a powerful story and the events causing her pain.She also depicts overcoming these obstacles, leading to a transformative read.The book separates Lindsay's tales on a chapter basis, leading to a choppily organized memoir with the overarching theme of the Woo-Woo.The Woo-Woo is a stand-in term for mental illness and describes those afflicted with mental disturbances or those who perform irrational behaviour.Throughout the book, it hereditarily advances through the family's women, sourcing from the author's maternal bloodline with her grandmother, Poh-Poh as the predecessor.As Lindsay reached the age of twenty, she questioned, "was the Woo-Woo an ineluctable punishment for the female descendants of Poh-
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.040 | 0.028 |
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".