How Do We Increase the Participation of Young Women in hiv/aids Activism? An Interview with Sisonke Msimang
Bibliographic record
Abstract
Sisonke Msimang (SM): One of the biggest challenges is not one that you can blame on young people themselves but one that has to do with the attitudes held by the people who work with youth. Young people are incredibly engaged and involved in HIV/AIDS activism at the service level although in developing countries they are not so active at the policy level. Quite often however the people who work with youth are extremely condescending towards them and limit their decision making power. It is a real challenge to get youth to attend regional meetings as they lack the credentials that more senior participants have. Once they are at these meetings they are often greeted enthusiastically by other members of the community but the actual structure of the meetings are not changed so that they can fully participate. In the African context youth participation also has the added challenge of communication difficulties. There are few networks that allow young people to travel and telephone and email infrastructure is often not as available to youth as it is to other organizations and individuals. In addition the quality of young women’s participation is often determined by the young men who are also participants in discussions and meetings. When young men are present there is often not space left for young women to also participate and speak—-young men do not often realize how much they talk and how much space they can take up. Importantly they often feel that discussing gender issues detracts from discussing youth issues. The attitude is that “we are so marginalized as it is why should we be favouring girls over boys?” So there’s a clear need to educate boys about gender. (excerpt)
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".