Intersections of gender and water: comparative approaches to everyday gendered negotiations of water access in underserved areas of Accra, Ghana and Cape Town, South Africa
Bibliographic record
Abstract
A large and growing body of literature suggests that women and men often have differentiated relationships to water access, uses, knowledges, governance, and experiences. From a feminist political ecology perspective, these relationships can be mediated by gendered labour practices (within the household, at the community level, or within the workplace), socio-cultural expectations (e.g. related to notions of masculinity and femininity), as well as intersectional differences (e.g. race, income, and so forth). While these relationships are complex, multiple, and vary by context, it is frequently argued that due to responsibility for domestic provision or other pathways, women may be particularly affected if water quality or access is compromised. This paper reports on a statistical evaluation of a 478 household survey conducted in underserved areas of Accra, Ghana and Cape Town, South Africa in early 2012. Interrogating our survey results in the light of the ideas of gender differentiated access, uses, knowledges, governance, and experiences of water, we open up considerations related to the context of each of our study sites, and also invite possible revisions and new directions for these debates. In particular, we are interested in the instances where differences among male and female respondents were less pronounced than expected. Highlighting these unexpected results we find it helpful to draw attention to methods – in particular we argue that a binary male–female approach is not that meaningful for the analysis, and instead, gender analysis requires some attention to intersectional differences (e.g. homeownership, employment, or age). We also make the case for the importance of combining qualitative and quantitative work to understand these relationships, as well as opening up what might be learned by more adequately exploring the resonances and tensions between these approaches.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.019 | 0.024 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".