Twenty-third meeting of the Committee of Experts of the Conference of African Ministers of Finance, Planning and Economic Development: Opening Statement by K.Y. Amoako Executive Secretary
Bibliographic record
Abstract
Opening Statement by K.Y. Amoako Executive Secretary of UNECA at the Twenty-third meeting of the Committee of Experts of the Conference of African Ministers of Finance, Planning and Economic Development. Mr. Amoako, on his remarks highlighted that, ECA has embarked on a number of initiatives aimed at increasing support to African countries on trade issues. For example, a new Trade and Regional Integration Division was created in 2003 to increase our capacity to respond to requests from member States; and an Interregional Advisory Services Office was established in Geneva in the same year to provide on-demand technical assistance to the WTO Geneva African Group. We have further enhanced technical support to member States by recently establishing the African Trade Policy Centre (ATPC), with the financial support of the Canadian government. Together with OECD/DAC, we have developed path-breaking tools for mutually monitoring development effectiveness, drawing on the conceptual framework already prepared by the two institutions and submitted to the NEPAD Steering Committee. An important aspect of placing our member States in our programming process involves feedback, monitoring and evaluation.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.070 | 0.028 |
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".