Unmasking difference: intersectionality and smallholder farmers’ vulnerability to climate extremes in Northern Ghana
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper examines intersectionality and climate vulnerability in Ghana’s Upper West Region. Located within the southern fringe of the West African Sahel, and inhabited largely by smallholder farmers, the Upper West faces recurring climate extremes. This paper asks, how do the intersections between different inequalities and power relations shape vulnerability to climate extremes? Evidence for the paper comes from intensive qualitative fieldwork. Focusing especially on lived experiences from four case studies, the paper demonstrates the textured ways in which masculinity ideals, health status, religion, gender, age, marital status, and poverty intersect to deepen farmers’ vulnerability to dry spells, flash floods, and after-storm recovery. Overall, the paper advances two interrelated arguments. Firstly, it argues that vulnerability analysis that focuses independently on gender, class, religion, and other characteristics, is insufficient because it risks homogenizing entire groups. Secondly, the paper argues that climate extremes do not always affect women more adversely than men. Indeed, dominant ideals of threatened masculinity can make men highly vulnerable during extreme climatic events. In the end, the paper concludes that if vulnerability analysis fails to unmask difference or move beyond binary gender categories, ensuing interventions may miss the real needs of countless individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it