Fighting Back in the War on General Purpose Computers
Bibliographic record
Abstract
EFF's Apollo 1201 project is a 10-year mission to abolish all DRM, everywhere in the world, within a decade. We're working with security researchers to challenge the viability of the dread DMCA, a law that threatens you with jail time and fines when you do your job: discover and disclosing defects in systems that we rely on for life and limb. Speaker Bio: Cory Doctorow (craphound.com) is a science fiction author, activist, journalist and blogger — the co-editor of Boing Boing (boingboing.net) and the author of the YA graphic novel IN REAL LIFE, the nonfiction business book INFORMATION DOESN’T WANT TO BE FREE and young adult novels like HOMELAND, PIRATE CINEMA and LITTLE BROTHER and novels for adults like RAPTURE OF THE NERDS and MAKERS. He works for the Electronic Frontier Foundation and co-founded the UK Open Rights Group. Born in Toronto, Canada, he now lives in London.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.176 | 0.107 |
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 source (direct Gemma or distilled Codex), 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".