Political Economy of Climate Compatible Development: Artisanal Fisheries and Climate Change in Ghana
Bibliographic record
Abstract
Summary Interest in prospects for policy processes that contribute to development, climate change adaptation and mitigation, known as ‘climate compatible development’, has been growing in response to increasing awareness of the impacts of climate change. This paper provides insight into the complex political economy of climate compatible development in Ghana's artisanal fisheries, a sector that has received comparatively little attention in climate change literature and policy processes. It focuses on two contentious policy areas where there is potential for climate compatible development, namely the subsidized premix fuel provided to artisanal fishermen, and mangrove protection. Regarding the premix subsidy, while there is theoretical scope for a ‘triple win’ outcome by removing the subsidy to reduce incentives to unsustainable fishing and supporting alternative policies, in practice this is highly problematic. Artisanal fishermen strongly oppose removing the subsidy on the grounds that it would damage their livelihoods, and do not have the confidence that they would be appropriately compensated for any hypothetical reform. Moreover, it is argued that removing it could have negative unintended consequences if fishermen are forced into alternative livelihoods that are themselves unsustainable. There is, however, a need to make considerable improvements to the distribution of the premix fuel so that it reaches the intended beneficiaries and is not siphoned off for contraband. Meanwhile, although improved mangrove protection could have significant ‘triple‐win’ benefits, this area suffers from a lack of funding and administrative coordination across ministries and agencies, leading it to be neglected. The case studies reveal, therefore, that the major constraint to climate compatible development is institutional failing, rather than a lack of policies per se. The paper emphasizes the need to conceptualize climate compatible development as a process which is dynamic across space and time, such that potential for triple win outcomes is fluctuate to vary according to changing circumstances. It is necessary to recognize, furthermore, that pressures from a number of actors, including those at the grass roots, may demand short term improvements to current problems rather than aspiring to triple win outcomes in the long term, creating a major challenge for climate compatible development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".