Closing the HIV and AIDS “Information Gap” Between Children and Parents: An Exploration of Makerspaces in a Ugandan Primary School
Bibliographic record
Abstract
In this study, we address the research question: “How might child-created billboards about HIV and AIDS help facilitate more open discussions between parents and children?" The premise of our study is that there may be considerable potential for using multimodal forms of representation in makerspaces with young children to create more open dialogue with parents about culturally sensitive information. Drawing on multimodal literacies and visual methodologies, we designed a makerspace in a grade 5 classroom (with students aged 9–10) in a Ugandan residential primary school. Our makerspace included soliciting students’ knowledge about HIV and AIDS as part of a class discussion focused on billboards in the local community and providing art materials for students to explore their understandings of HIV and AIDS through the creation of billboards as public service announcements. Parents were engaged in the work as audience members during a public exhibition at the school. Data sources include the billboards as artifacts, observations within the makerspace, and interviews with parents and children following the public exhibition. The findings show that, for parents and children, the billboards enhanced communication; new understandings about HIV and AIDS were gained; and real-life concerns about HIV and AIDS were made more visible. Although these more open conversations may depend to some degree on family relationships more broadly, we see great potential for makerspaces to serve as a starting point for closing the HIV and AIDS information gap between children and parents.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".