Jordan Peterson is Back! - Bret Weinstein's DarkHorse Podcast
Bibliographic record
Abstract
Jordan Peterson is an author, YouTube lecturer, and professor of psychology at the University of Toronto. Buy Jordan's new book: Beyond Order - 12 More Rules for Life: https://read.amazon.com/kp/embed?asin=B08NP6881Kpreview=newtablinkCode=kperef_=cm_sw_r_kb_dp_8ZSEX3G3CRRHS6Y1N9JK Find Jordan on his website: https://www.jordanbpeterson.com Find Jordan on Twitter: @jordanbpeterson --- Find Bret Weinstein on Twitter: @BretWeinstein, and on Patreon. Please subscribe to this channel for more long form content like this, and subscribe to the clips channel @DarkHorse Podcast Clips for short clips of all our podcasts. DarkHorse merchandise now available at: store.darkhorsepodcast.org Theme Music: Thank you to Martin Molin of Wintergatan for providing us the rights to use their excellent music. Support the show (https://www.patreon.com/bretweinstein)
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.572 | 0.015 |
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".