Solidarity, with Suresh Grover, Shabna Begum & Karis Campion
Bibliographic record
Abstract
AUDIO CONTENT WARNING: description of extreme racist violence.In 1993, Black British teenager Stephen Lawrence was murdered in a racist attack that sparked a long fight for justice and led the UK to ask questions of itself and its institutions.Three decades on -with The Runnymede Trust's Shabna Begum, and Suresh Grover of The Monitoring Group -Karis Campion of the Stephen Lawrence Research Centre hosts this special episode to ask: who are we now?What happened to anti-racist solidarity and how can it progress?Karis and guests reflect on the fragmentation of "political blackness", "monitoring" as a racial act inspired by The Black Panther Party, and the importance of showing systemic racism while doing justice to individual lives.Plus: what does social media offer to anti-racism when the internet provides fertile ground for prejudice?And what are the costs of fighting for change in an unjust world?
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 teacher head, 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".