Decolonial Feminism, Entrepreneurship, and the Use of Bicycles for Development in Northern Uganda
Bibliographic record
Abstract
This study aims to provide deeper understanding of the “grand narratives” surrounding the promise and potential that bicycles and entrepreneurship are assumed to have for women in the Global South. Decolonial feminism is used to contest Eurocentric narratives underlying bicycles and entrepreneurship and to provide nuanced insight into how women in Northern Uganda resist the oppression resulting from colonialism and patriarchy. Eighteen women from two communities shared their lived experiences of using bicycles received from a nongovernmental organization. The findings revealed that bicycles are used by women for income-generation and business activities that largely align with dominant Westernized narratives of entrepreneurship that reproduce capitalist modes of thinking. Histories of colonialism and coloniality influence gendered roles and identities that are reflected in the work women do. However, the self-organization of women has led to bicycles and “bicycle savings groups” being used by women to promote unity and advocacy that resist patriarchal oppression and may alter gender relations. This paper contributes to existing literature on gender, mobilities, and entrepreneurship, demonstrating the usefulness of decolonial feminism to reveal the threads of oppression experienced by women while at the same time centering subaltern women’s agency. The findings unveiled the need to better account for heterogenous experiences of mobilities and entrepreneurship, particularly those of subaltern women who are framed as the beneficiaries of bicycles through grand narratives.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".