Government Contracting: Federal Efforts to Assist Small Minority Owned Businesses
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
A letter report issued by the Government Accountability Office with an abstract that begins "While their views varied to some degree, federal agency officials and advocacy groups GAO contacted identified a number of challenges that small, minority-owned businesses may face in pursuing federal government contracts. For example, officials and advocacy groups pointed to a lack of performance history and knowledge of the federal contracting process as significant barriers. Officials from advocacy groups cited additional challenges, such as difficulty gaining access to contracting officials and decreased contracting opportunities resulting from contract bundlingthe consolidation of two or more contracts previously performed under smaller contracts, into a single contract. Officials from agencies that accounted for 70 percent of federal contracting with small, minority-owned businesses(the Departments of Defense, Health and Human Services, and Homeland Security, and the General Services Administration) told GAO that they conducted outreach to help small, minority-owned businesses with these challenges. Their outreach efforts include one-on-one interviews between contracting office staff and businesses seeking federal contracts. Linguistic and cultural barriers were identified as a challenge on a limited basis."
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| 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