Capacity development on gender responsive economic policies for inclusive development in Africa
Bibliographic record
Abstract
The African Institute for Economic Development and Planning (IDEP) in collaboration with The United Nations Development Program Regional Service Center for Africa (UNDP-RSCA), and the financial support of the Government of Canada has organized in Dakar, a face-to-face training on "Gender-responsive economic policy management within the context of the post-COVID19 recovery”, from 08 to 12 May 2023. The face-to-face training was a follow-up to an online training that took place from 23 January to 17 February 2023 and attended by 318 participants in critical policies issues such as gender and macroeconomics, gender responsive analysis, gender and trade, and gender and gender budgeting.
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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.071 | 0.009 |
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".