OAU Conference on a Landmine-free Africa: The OAU and the Legacy of Anti-personnel Mines, Johannesburg, South Africa, 19–21 May 1997
Bibliographic record
Abstract
In some ways, and with hindsight, the Johannesburg meeting may come to be seen as the watershed in the Ottawa process, as African governments sought to take responsibility for tackling the mines crisis in the region. If African participation in the Oslo Diplomatic Conference was both visible and highly effective, this must be put down, in part at least, to the momentum created beginning with the ICBL Conference in Maputo in February, increasing with the ICRC seminar in Harare in April, and culminating with the OAU Conference in Johannesburg. With the exception of one African government, all others were of a single mind, determined to ensure the total prohibition of anti-personnel mines which they saw as essential to stem the continuing proliferation of the weapon. This solidarity helped to ensure that the treaty ultimately adopted was clear and unequivocal. The Provision of Assistance to Mine Victims Dr Chris Giannou Health Operations Division, International Committee of the Red Cross 19 May 1997 Algeria, Angola, Botswana, Burundi, Chad, Congo, Djibouti, Egypt, Eritrea, Ethiopia, Guinea Bissau, Liberia, Libya, Malawi, Mali, Mauritania … No: this is not a roll-call of the Member States of the Organization of African Unity. Morocco, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Sierra Leone, Somalia, Sudan, Swaziland … This is a list of regions ofthe African continent which are or have been polluted to a varying extent by landmines. Tanzania, Tunisia, Uganda, Western Sahara, Zaire, Zambia, Zimbabwe. Many of these mines date back to World War II, others to the struggle for independence and the wars of decolonization, yet others to post-independence conflicts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".