S1:E10 - Racism & The Criminal Legal System - Prof. Julius Haag
Bibliographic record
Abstract
Episode Summary What happens when a racial profiling researcher is himself stopped by police for no reason at all and “carded”? Julius Haag shares about his personal experiences with Toronto police and his research into racism in the criminal justice system: how Black people are simultaneously over-policed and under-protected. Episode Notes Content Note: discussion of racism against Black, Indigenous and people of colour; police use of force and police-involved deaths; gun violence; incarceration; poverty; and mental health challenges. 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) "District 99" by Grand_Project CBC News: The National, "'Unprecedented' report released on racial profiling by Toronto police" "Connect The Dots" by Cosmo Lawson CTV News, "Toronto police have proven 'incapable' of protecting Black community: expert" "Racing Forward" by Grayson DeSmet "Dark Somber Serious" by Ashot-Danielyan-Composer CBC News, "What systemic racism in Canada looks like" "Conspiracy" by Mark Fabian "Newborn Earth" by INPLUSMUSIC "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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.067 |
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".