The discursive construction of adaptation subjects via the Ada Sea Defense System in the Volta River Delta of Ghana
Bibliographic record
Abstract
As climate adaptation gains international prominence as one means for addressing climate change, it remains critical that just and equitable outcomes are maintained as adaptation technologies are deployed across various target populations. In this vein, subjectivity has been problematized by climate change adaptation scholars as a concept that needs further attention to understand the political nature of climate change adaptation. Extending frameworks of environmentality to cases of climate change adaptation, we engage the term adaptation subjects to distinguish individuals whose interests and desires align with broader understandings and goals of climate change adaptation. In this research, we situate the co-production of livelihoods and climate change adaptation interventions as projects of rule to understand subject-formation. Such an analysis allows for a move beyond econocentric framings of livelihoods that privilege material outcomes to also engage with the socio-political realities of these livelihoods and climate change adaptation more broadly. We apply the Livelihoods as Intimate Government approach to a case study of the Ada Sea Defense System in the Ada East District of the Volta River Delta of Ghana as a climate change adaptation project of rule, in order to illustrate the ways this adaptation technology discursively constructs (or not) different residents as adaptation subjects. Understanding the Ada Sea Defense System as a technology of adaptation constituted through socio-political practices has the potential to promote justice and equity when designing, implementing and evaluating such technologies in the future.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".