Engendering the blue economy : offshore oil extraction and the livelihoods of women in 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
Ghana joined the league of oil and gas producing countries in 2007 when oil was discovered in the Gulf of Guinea. Through the years, however, concerns have emerged over the impacts of oil and gas activities on coastal livelihoods, especially since the benefits of extraction do not seem to trickle down to these communities. This thesis employs the Feminist Political Economy framework to examine the gendered disparities embedded in relations between offshore oil extraction and livelihoods of women in Ghana. Through an exploratory approach and a mixed methods design, I reveal how the intersection of culture, geography, politics, race and class foster the dispossession of coastal women. Among other findings, this thesis reveals that fishing is still the main source of livelihoods, and a culturally import source of food for the Western Region. It also shows that the advent of oil in the region has not improved but worsened women's livelihoods.
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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) | 0.001 | 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