The Minds of Boys: Saving Our Sons from Falling Behind in School and Life
Bibliographic record
Abstract
The Minds of Boys In this fascinating and practical book, Michael Gurian-the author of the best-selling The Wonder of Boys-and Kathy Stevens show parents and teachers how to help our boys overcome their current classroom obstacles and failures. They offer clear-cut step-by-step guidance to help boys fulfill themselves, use their intelligence, work with their unique natural gifts, expand every bit of their potential, and ultimately succeed in life. The Minds of Boys also presents a scientifically researched, field-tested program for helping boys learn the academic basics: reading, writing, math, and science. Drawing from the latest gender-based brain science and tested by the Gurian Institute and school districts across the United States, Canada, and Australia, the program speaks to specific differences in the way boys and girls learn, the best learning environment for boys' brains, how to help undermotivated and underperforming boys, how to use the arts and athletics to teach boys, how to teach and care for sensitive, aggressive, restless, or bored boys, and how to utilize the option of single-gender education at crucial periods of a son's life. The Minds of Boys emphasizes that our schools cannot fix the problems our boys face without families becoming a centerpiece for the solution. Detailing how parents, extended family, teachers, coaches, and mentors can work together, this proven classroom program can help confront the current crisis in boys' education so that all our sons achieve success in life.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".