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 Onusko's book "Boom Kids: Growing Up in the Calgary Suburbs, 1950-1970", shows what the lifestyle was like in the Calgary suburbs, more specifically in Banff Trail during the period of 1950 to 1970.Onusko is known for his work gathering information about what happened in Canadian neighborhoods after the Second World War.Yet in this book, his research gives substantial weight to the perspective of children's experiences in suburban Banff Trail with information gathered from that stage of Calgary's history, and personal testimonies of today's adults who were children in the postwar era.As a result, the book adopts a focus on how children and adolescents played a fundamental role in the creation of a social identity that existed in the second half of the twentieth century in Canadian neighborhoods.Onusko's book through his meticulous gathering of reliable sources of information facilitates the reader and the academic audience the visualization of what life was like in those times, when the effects of the Second World War were still persevering in society, and where the beginning of a new social group reflected in life in the neighborhood, family economic structures, and the new approach to education were influenced by the activities of children and young people contributed to the creation of this new social identity.By comparing life today with life back in the 1950s, it can be easy for readers to see what
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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 | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 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".