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
Lindsey Wong's book, "The Woo-Woo," is an interesting narrative of personal events that occurred throughout her lifetime.She takes readers through a stream of emotions, making sure to mix in a sense of humor, sadness, and pity throughout its context.Each account of her life is brought forward with so much detail, that envisioning what is happening in your mind is almost effortless.In doing so, Wong allows her audience to absorb as many aspects of life as possible.This is her way of opening up minds to the boundless reality of what makes a family and what it means for family members to endure with one another.Wong does well to incorporate certain points of interest of sociologists about family, parenting, self-esteem, culture, and mental health by depicting her own experiences with them.In turn, these experiences combine to create her memoir of events that helped shape the person she has become today.This memoir finds its foundation based on family, as Wong describes her parents' methods of raising her.In today's modern era, at least in Western culture, a family consists of people related by blood who are in the best interest of one another and help support each other into becoming model citizens within their society.This basic concept of what a family is supposed to be is quickly discarded at the beginning of the memoir.Wong commences her description of her parents with an argument they had when she was a little girl, where they yelled, screamed, and even threw
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.026 |
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".