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
The control of corruption is an important element of governance and a stated goal of many governments. Legislative oversight is an acknowledged mechanism for controlling corruption, but little research has been undertaken on this subject, and national anticorruption strategies generally ignore the legislature. This article addresses the question of whether legislative oversight helps to curb perceived corruption, and if so, how. Statistical analysis using data from a global survey of 82 legislatures found that the presence of legislative oversight tools explains a major proportion of the variance in perceived levels of wrongdoing in countries with presidential forms of government, but much less in countries with semipresidential governments and less yet again in parliamentary systems. The analysis also found that the effectiveness of legislative oversight instruments varies by form of government. In presidential countries the most important instruments are committee hearings, hearings in plenary, and ombuds offices; in semipresidential countries they are question time, interpellations, and ombuds, while in parliamentary systems interpellations are the most important. These findings demonstrate that while the oversight apparatus is useful in helping curb malfeasance, not all tools are equally effective, and what works for some forms of government may not work as well, or at all, in other systems. Clearly, the "one size fits all" approach is inadequate when it comes to legislative corruption control.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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