Book Review of Traig, J. (2019). Act Natural: A Cultural History of Misadventures in Parenting. New York: HarperCollins Publishers.
Bibliographic record
Abstract
Jennifer Traig's "Act Natural" is an encapsulation of the many difficulties and hardships faced by parents, while also serving as great insight into the many cultural and historical methods of parenting.Primarily relying on history to highlight the many mishaps parents encountered while raising their children, Traig delivers her findings on the evolution of child rearing in an informative, yet humourous manner.Using her own experiences of being a mother, Traig emphasises that raising children is no walk in the park and is often accompanied with nothing short of exhaustion.Focussing strongly on the history of Western and Medieval parenting, Traig extensively writes about the prevalence of infant and maternal mortality, alloparenting, and children's books, to name a few.Not only does Traig somewhat criticize and question past approaches to parenting, but she also recognizes that some of the techniques are actually very helpful, and still stand today with modern parenting.Traig organizes her book into ten chapters, each of which focus on different segments of parenting.Traig talks a great deal about alloparenting, which is the practice of leaving your kids to someone else (p.2).Alloparenting was a very common practice among many cultures, and was primarily practiced by the rich, who wanted nothing to do with their children.Raising children requires a great deal of resources, time, and attention, which is something not all parents were
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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 | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.031 |
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".