Episode 124 – white rage in Nova Scotia: terrorism or genocide?
Bibliographic record
Abstract
In this episode, Sandy and Nora talk about why taking action in support of Mi’kmaq fishers, and Indigenous struggles everywhere, is so critical. They also talk about seniority in the labour movement, and how eliminating seniority isn’t going to fix systemic racism in the workplace. Contest is closed but you can buy merch here still: https://twitter.com/amybeatrice/status/1317161330260979713 Nora’s book launch RSVP: https://www.eventbrite.ca/e/billets-noras-55-hour-book-launch-open-house-pandemic-nightmare-edition-125505517381 RESOURCES: Donations: https://t.co/qp5x3vOqcb?amp=1 Twitter thread of ideas: https://twitter.com/TheAgentNDN/status/1317325273730371584 How others are helping: https://www.cbc.ca/news/indigenous/mi-kmaw-fishers-creative-support-1.5770229?__vfz=medium%3Dsharebar
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.704 | 0.026 |
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".