Recommendations to Reduce Sexual Violence Rates in Haitian IDP Camps
Bibliographic record
Abstract
In January 2010, a magnitude 7.0 earthquake tore through the area surrounding Haiti’s capital of Port-au-Prince, destroying much of the city’s already fragile infrastructure. Over 222,570 people were killed and 300,572 injured. An additional 2.3 million—almost a quarter of the population— were displaced and now live in roughly 1,300 internally displaced person (IDP) camps.The camps are constructed mostly of tarpaulins, have limited public shower and toilet facilities, and lack adequate lighting and sanitation. These living conditions exacerbate the already high risks of sexual violence in Haiti. As sexual violence is severely underreported, no official statistics exist for the levels of rape in IDP camps in Haiti. However, there is evidence that sexual violence is rampant. In fact, a University of Michigan study estimates that 3% of the female Haitian population in IDP camps has experienced sexual violence since the earthquake. Although $5.5 billion have been pledged to rebuild Haiti in the months following the earthquake, aid absorption is low and disbursement is slow. In fact, the few Haitian groups that are working to address sexual violence have received little to no funding in the last ten months. This paper is a response to the United Nations Stabilization Mission in Haiti’s (MINUSTAH) decision in September 2010 to launch a campaign to eliminate sexual violence in Haitian IDP camps. In order to successfully carry out a campaign to end sexual violence, MINUSTAH must involve local Haitian women and non-government organizations (NGOs) in all phases of planning and implementation. In doing so, MINUSTAH should provide practical training programs to women and men living in the IDP camps and assist them to form autonomous security brigades in order to protect women and prevent sexual violence.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.037 | 0.012 |
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".