Book Review of Traig, J. (2019). Act Natural: A Cultural History of Misadventures in Parenting. New York: HarperCollins Publishers.
Bibliographic record
Abstract
A Cultural History of Misadventures in Parenting" takes a comical stroll through history detailing out-of-touch practices that occurred through the early stages of an infant's life, from birth to surviving the first few years, consisting of teething, potty training, the so-called "terrible twos" and onwards.She covers such themes as the evergrowing amount of contradicting parenting advice, gender roles in parenting and the difference in expectations set out for the father and mother, the evolution of understanding child development, and parenting trends and fads.She explores these themes by observing the historical trends, following them and their supporting theories and experiments throughout time, and adding comical remarks on their sometimes outlandish methods.She also often adds anecdotes and reflections on her own parenting choices that make the book feel more personal, like you're chatting with her about parenting.She discusses the good, the bad, and the ugly sides of parenting, along with the joy that it brings to one's life while providing a research background to support the commonly felt sentiments, overall leaving the reader entertained, informed, and perhaps a little more prepared for bringing a child into the world.On the theme of contradicting parenting advice, she has an individual chapter devoted to
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.037 |
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".