Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As of 2007, more than 9.25 million people were imprisoned worldwide. Almost half of the persons imprisoned are in the United States, China and Russia. The United States has more persons in prison per capita than any country in the world. Prisons The World Over offers a comprehensive overview of prison demographics and conditions for each of the following countries: United States, Canada, Argentina, Brazil, France, Germany, Great Britain, Italy, Sweden, Hungary, Poland, Russia, Israel, Egypt, Iran, Nigeria, South Africa, India, China, Japan, and Australia. The book includes reports on the number of prisoners, the rate per population, the percent of female prisoners, the number of penal institutions and their occupancy level, and the number of privately run prisons Also reported are the offenses for which the inmates are interred, the average length of incarceration, the availability of parole, conditions in the prisons, the availability of educational and work programs, provisions for children of female prisoners, the availability and quality of medical care, the characteristics of the prison staff, the visitation rights of prisoners, and the presence and treatment of political prisoners.
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.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it