A roundtable discussion on decentralization, local development and women’s empowerment
Bibliographic record
Abstract
The experiences from Africa, Asia, Latin America and North America show how women at the local level have innovated existing tools, mechanisms and methodologies, to better address their needs and aspirations, often in the context of poverty and marginalization. However, many issues remain open, including how to expand, consolidate and scale up their achievements at the local level so that they can influence processes and policies that are determined at national or international levels. Universitas Forum invited the members of the editorial board for this special issue of our journal – coming from the worlds of research, policy and practice – to reflect on some of these open questions, taking into account the experiences published here, through a round table discussion.
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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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.023 | 0.019 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".