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
Why does corruption persist over long periods of time? Why is it so difficult to eliminate? Suggesting that corruption is deeply rooted in the underlying social and historical political structures of a country, Uslaner observes that there is a powerful statistical relationship between levels of mass education in 1870 and corruption levels in 2010 across 78 countries. He argues that an early introduction of universal education is shown to be linked to levels of economic equality and to efforts to increase state capacity. Societies with more equal education gave citizens more opportunities and power for opposing corruption, whilst the need for increased state capacity was a strong motivation for the introduction of universal education in many countries. Evidence for this argument is presented from statistical models, case studies from Northern and Southern Europe, Asia, Africa, Latin America, the United States, Canada, Australia, and New Zealand, as well as a discussions of how some countries escaped the 'trap' of corruption.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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