Book Review of Onusko, James. A. (2021). Boom Kids: Growing Up in the Calgary Suburbs, 1950-1970. Waterloo: Wilfred Laurier University Press
Bibliographic record
Abstract
James A. Onusko's book, "Boom Kids: Growing up in the Calgary Suburbs, 1950Suburbs, -1970," ," studies the interplay of class, ethnicity, race, gender and culture and how these factors play a role in influencing postwar suburbia for children, adolescents, and families.Using a collection of media, interviews, images and other data, Onusko highlights how each individual had no single defining experience in postwar suburbia, including those who spent their childhoods living under the same roof.Onusko looks at several factors that defined postwar suburbia for the families of Banff Trail.Some of these factors include: (1) the changing landscape from rural to urban life; (2) the working lives of those growing up in the suburbs and how class and race came into play; and(3) the previous wars and their effects on children in the classroom.Looking at these three factors and the interplay between them, Onusko highlights how growing up in suburbia in Banff Trail between 1950 and 1970 was a shared but individual experience.Onusko notes that suburban areas became increasingly more common for children to grow up in the postwar era, stating that "in the first post-Confederation census in 1871 over 80 percent of children lived in rural households, by 1971, there was a near reversal of this, with over 75 percent living in urban centres," (p.21).This could attribute to the fact that there was an increase
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.066 | 0.039 |
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".