Bibliographic record
Abstract
In the opening scene of Outspoken, Sima Samar details the devastating attacks on a girls’ school in the Hazara neighbourhood of Dasht-e Barchi in Kabul. The attack took place on 8 May 2021—less than one month after US President Joe Biden announced the unconditional withdrawal of US troops from Afghanistan—and killed or injured more than 300 schoolgirls and bystanders. The neighbourhood in question was already reeling from years of targeted attacks, including a devastating massacre at a maternity ward. Samar views the school attack as a grim forecast of the end of Afghanistan's democratic experiment and a representation of the violence that the US–Taliban Doha deal unleashed. She criticizes the corruption of Afghan leaders and reflects on the resilient yet harrowing reality of Afghan women, who ‘have had to build a new nest over and over again’ due to decades of conflict, displacement, foreign intervention, violent patriarchy and betrayal (p. 289).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.011 |
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".