African Trade Policy Centre hailed for its evidence-based advisory services
Bibliographic record
Abstract
The African Trade Policy Centre (ATPC) of the Economic Commission for Africa (ECA) held the first Steering Committee Meeting (SCM) of its fourth programme cycle in Dakar, Senegal. The hybrid event was hosted by ECA’s African Institute for Economic Development and Planning (IDEP) and preceded by a Partners Meeting that was held on 25 May 2021. At the opening of the event, Khadija Jarik, Vice-Chairperson of the Steering Committee and representative of Global Affairs Canada in Addis Ababa, expressed Canada’s unwavering commitment to ATPC, which it supported from its establishment in 2003. Its observed that, through its support to ATPC, Canada hopes the current phase of the project will help African countries put in place domestic reforms necessary to effectively implement their AfCFTA commitments. She also expressed satisfaction that the new programme cycle has introduced an environment work stream under which the ATPC carries out a strategic environment assessment in supporting implementation of the AfCFTA.
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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 | 0.153 | 0.336 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.018 | 0.021 |
| Insufficient payload (model declined to judge) | 0.148 | 0.043 |
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".