Bibliographic record
Abstract
Acknowl edgmentsWe begin this text by acknowledging that we have conducted our scholarship and teaching on the unceded ancestral territories of vari ous Indigenous peoples, lands today identified as Canada and the United States.It can be easy for us to dismiss the idea that events from the past could matter to us here in the pre sent.But studying the history of colonialism-the cultural, emotional, and physical genocide of peoples around the world-reminds us that to understand the injustices of today we must recognize their connection to injustices of the past.We offer our deepest re spect to Elders and knowledge keepers both past and pre sent.We extend our heartfelt thanks to the friends and colleagues who have supported us with this proj ect, especially those who so generously gave their time and expertise to read and offer feedback to the vari ous editions of the book.Big thanks to our amazing research assistant Sabrina Ngo, whose careful work double-checking our references and helping update the statistics was invaluable support in the creation of this third edition.Thank you to Katherine Streeter for her artwork
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.092 | 0.020 |
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".