Book Review of Barkin, Janna. (2017). He's always been my Son: A Mother's Story about Raising her Transgender Son. Philadelphia: Jessica Kingsley Publishers.
Bibliographic record
Abstract
Always Been My Son", is a book that describes the life of Amaya Barkin, a transgender individual and his family.This book is nonfiction and is written from a first-person point of view, with Janna, Amaya's mother, narrating the bulk of the chapters.Other family members and friends of the family also provide their perspectives on the impact of Amaya's change.This book takes place over the course of several years and discusses Amaya's childhood through to his college years.The author seeks to provide information regarding the transgender transformation process and encourage empathy and understanding for transgender individuals.Janna Barkin's goal when writing this book was to provide positive guidance and motivation to those going through a similar journey (p.14).The author highlights the challenges of being a transgender individual, including the stigma and stress of coping in a binary world, in hopes of creating more understanding of what transgender people experience on a daily basis.Janna Barkin also discusses the positive experiences and the support from family, friends and agencies that she and her family received.A significant theme throughout this book is the stigma associated with being transgender and the impact on individuals who identify as such.The transgender identity challenges the tra-
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.029 |
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".