Boys Will Be _: The Online Lives of Boys Who Are Embracing Positive Masculinity
Bibliographic record
Abstract
We give a heartfelt thanks to the boys brave enough to be vulnerable and honest with us as they shared their personal experiences.This report is directly informed by the experiences and issues of the boys themselves, meaning that their thoughts, ideas and feelings are all their own.Please note that all extracts from surveys and focus groups are inserted as shared by the original respondent, including typographical errors.Names have been substituted. ABOUT NEXT GEN MENFounded in 2014, Next Gen Men is a small-but-mighty Canadian nonprofit dedicated to a future in which boys and men experience less pain and cause less harm.We bring together perspectives from across North America, across genders, and across specialties to talk about why we all have a stake in the future of masculinity.At Next Gen Men, we are champions of hope, and workers for change.Find us in your community, your classroom, your workplace, online, across Canada, the U.S. and anywhere you find our community.For more information, visit nextgenmen.ca.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".