World Bank Policy on Access to Information Progress Report : January through March 2011
Bibliographic record
Abstract
This report follows the World Bank's first two progress reports on the implementation of its Policy on Access to Information (AI).The Report reviews the AI Policy implementation results for the period of January 1 to March 31, 2011. In this third quarter the Bank continued its efforts to increase and improve public access to information in the Bank's possession. The Bank proactively disclosed 3,836 new documents and reports, posting them for public access in the Bank's Documents and Reports public database. This number includes 101 restricted documents that have been declassified and disclosed for public access. It also includes 978 Implementation Status and Results Reports, a 1240 percent increase in the number of ISRs disclosed when compared with the First Quarter, and a 64 percent increase compared with the Second Quarter. Since the AI Policy's effectiveness in July 2010, the public has viewed more than three million pages in Documents and Reports.Of the requests that were completed in the third quarter, 71 percent of the cases were completed within the AI Policy's 20 working day standard (for cases not involving special circumstances that require additional time to process). The 71 percent averaged eight working days. In the third quarter, the access to information learning program continued to promote staff knowledge necessary for the successful implementation of the AI Policy agenda.The next AI Policy implementation report will be the AI Policy Annual Report, which will provide a cumulative review of the first 12 months of implementation, covering the period of July 1, 2010, through June 30, 2011.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".