Memories and Motherhood in the Rhythms of Ugandan Computing
Bibliographic record
Abstract
Based on ethnographic research in the computing communities of Ugandan universities, we advance a feminist and decolonial critique of the dominant chronopolitics of globalizing technologies. Our analysis starts with participants recounting their childhood memories of growing up in rural poverty under the shadow of rebellion wars. We show how the future promises of computing make sense in reference to this past. The same chronopolitics of pitching the past against the future is used by the global computing and donor development industry, and Uganda’s governing regime, which disguises the symbolic and physical violence of the evacuated present. In coping with the precarities of the present, we show how female computing researchers build enduring “near futures” through work that corresponds to the historical and symbolic role of Ugandan women in the domestic realm. And yet the chronopolitics of global computing syncopates with that of “near futures.” Women’s communal roles are written into computing and computing is made possible and doable in Uganda through the gendered logics of care practised in the present. The paper thus contributes to an expanding literature on computing in Africa, by providing a temporal analysis that recognizes women’s roles in more substantive ways.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".