Round table report: Advancing regional social integration, social protection, and the free movement of people in Southern Africa
Bibliographic record
Abstract
The round table on “Advancing regional social integration, social protection, and free movement of people in Southern Africa” was organized as part of the conference “Regional governance of migration and social policy: Comparing European and African regional integration policies and practices” held at the University of Pretoria (South Africa) on 18–20 April 2012, at which the articles in this special issue were first presented. The discussion was moderated by Prince Mashele of the South African Centre for Politics and Research and the participants included: Yitna Getachew, IOM Regional Representative for Southern Africa, Migration Dialogue for Southern Africa (MIDSA); Jonathan Crush, University of Cape Town and Balsillie School of International Affairs, Canada, representing the Southern Africa Migration Program (SAMP); Vic van Vuuren, Director of Southern African ILO; Vivienne Taylor, South Africa Planning Commission; Sergio Calle Norena, Deputy Regional Representative of UNHCR; Laurent De Boeck, Director, ACP Observatory on Migration, Brussels; Wiseman Magasela, Deputy Director General Social Policy, South African Department of Social Development; and Sanusha Naidu, Open Society Foundation for South Africa.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.077 | 0.014 |
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".