Economic abuse among Ghanaian women in intimate relationships
Bibliographic record
Abstract
Domestic violence, including economic abuse, is a global problem with far-reaching implications for women. Economic abuse occurs when an intimate partner deprives or threatens to deny their partner access to, and control of, financial and economic resources. Emerging evidence indicates that women in sub-Saharan Africa, including Ghana, experience high levels of economic abuse, and that it takes many forms. Notwithstanding, academic research on this topic remains scant, and very few studies document women's lived experiences of economic abuse. This dissertation contributes to the literature by examining the lived experiences of women facing economic abuse in the Greater Accra, Ashanti, and the Upper East regions of Ghana. This study used qualitative in-depth interviews and feminist theory to explore the causes, consequences, and coping strategies of 16 female survivors of economic abuse in Ghana. Results indicate that economic abuse is a common experience for Ghanaian women, although they were often unaware of it. Women narrated experiences of economic exploitation, deprivation, and sabotage affecting various aspects of their lives. While some women had had their employment sabotaged by their male partners, others had experienced financial extortion by their partners. Husbands’ extramarital affairs, lack of interest in the family or apathy, drunkenness, jealousy, and cultural factors were major causes of these types of abuse. Economic abuse negatively affected female survivors' jobs, businesses, and food security, and led to physical violence and adverse health implications. Women coped with these types of violence by relying on external family networks, religion, and theft from husbands, while others trivialized their experiences. Policymakers need to implement programmes that educate women about economic abuse and empower them to be economically and financially self-sufficient.
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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 | 0.001 | 0.003 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".