S1:E7 - Trauma and The Criminal Justice System - Dr. Gabor Maté
Bibliographic record
Abstract
Episode Summary World-renowned trauma expert Dr. Gabor Maté, author of "The Myth of Normal", exposes how our criminal justice system gets it horribly wrong by exacerbating trauma, and what we need to do differently. He shares about his frontline experiences in Vancouver's Downtown Eastside and being a witness himself in a criminal trial. Episode Notes Content Note: general discussion of trauma including childhood trauma, graphic details of a violent assault of a child by his older brother, mental health, substance use, unregulated drug deaths, incarceration, racism, poverty, suicide, intergenerational trauma, Residential Schools and ongoing colonial violence against Indigenous people. Click here for mental health support resources. Order your copy of Indictment: The Criminal Justice System on Trial (Aevo UTP, 2023) Visit www.benjaminperrin.ca for the latest news and upcoming events We are grateful for support from the University of British Columbia and Law Foundation of British Columbia ----------- Credits: "The Notion" by Northern Points (Intro) "Midnight" by Lexin_Music CBC News: The National, "Cycle of trauma from residential schools lasts for generations" PBS NewsHour, "Childhood trauma impacts millions of Americans, and it’s having devastating consequences" "Racing Forward" by Grayson DeSmet "Conspiracy" by Mark Fabian BBC News, "The PTSD brains of children & soldiers" "Behind the Mask" by Mark Fabian "Inspirational Sentimental Romantic" by Lexin_Music "Tense Detective Looped Drone" by Daddy_s_Music "Morning Garden - Acoustic Chill" by Olexy "Truth and Reconciliation Commission still demanding answers" by CityNews "Dramatic Atmosphere with Piano and Violin" by UNIVERSFIELD "Epic Heart" by Daddy_s_Music CBC News: The National, "Tracking deadly encounters with Canadian police — CBC News: The National" "Chaos in the Outback" by septahelix "Racing Forward" by Grayson DeSmet "Chaos erupts in House of Commons as Trudeau, Poilievre exchange personal attacks" by Global News "Inspiring Cinematic Ambient" by Lexin_Music "Price of Freedom" by Daddy_s_Music CBC News: The National, "Prison Guards and PTSD: High Rates With Little Attention" "Leva-Eternity" by lemonmusicstudio "The Clermont" by Flash Fluharty "A Call to the Soul" by Markotopa "Everyday Adventures" by Sound and Vision (Outtro)
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.014 |
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; both teacher heads agree on what is shown here.
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".