Financial Audit: Material Weaknesses in Internal Control over the Processes Used to Prepare the Consolidated Financial Statements of the U.S. Government
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "For the past 11 years, since GAO's first audit of the consolidated financial statements of the U.S. government (CFS), certain material weaknesses in internal control and in selected accounting and financial reporting practices have prevented GAO from expressing an opinion on the CFS. GAO has consistently reported that the U.S. government did not have adequate systems, controls, and procedures to properly prepare the CFS. GAO's December 2007 disclaimer of opinion on the fiscal year 2007 accrual basis consolidated financial statements included a discussion of continuing control deficiencies related to the preparation of the CFS. The purpose of this report is to (1) provide details of continuing material weaknesses, (2) recommend improvements, and (3) provide the status of corrective actions taken to address the 81 open recommendations related to the preparation of the CFS that GAO reported in July 2007."
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.
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 | 0.060 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".