Bibliographic record
Abstract
In this interview, 12-year-old Wren Kauffman shares his earliest memories of "not feel[ing] right" in his body and how he conveyed this powerful sentiment to his parents. Wren and his mother Wendy discuss the transgender journey their family has gone on, which initially started by contacting the Institute for Sexual Minority Studies and Services at the University of Alberta. Wren recounts how he told friends and classmates that he was transgender, talks about the support and openness he has received from teachers, friends, and schools, and of the critical importance of acceptance. Issues such as bullying, gender-neutral spaces, and diversity are also discussed. In addition, Wendy emphasizes the key role education plays in the inclusion of transgender children: "If we can start from a place of education, and explain that there is a really wide kind of variety of different ways that people can be born, that’s going to help society and people in general understand that transgender people are in the world."
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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.049 | 0.091 |
| Insufficient payload (model declined to judge) | 0.007 | 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".