Performative Vulnerability: Climate Change Adaptation Policies and Financing in Kiribati
Bibliographic record
Abstract
This paper explores some of the perverse effects of climate change adaptation policies and financing in the Republic of Kiribati, a low-lying island nation in the Central Pacific. I examine how encounters between financiers and government officials might produce vulnerability to climate change. I draw throughout from field research conducted in Kiribati, an archetypical ‘vulnerable-to-climate-change’ place, and a preeminent site for experimentation in climate change adaptation. By discussing several instances where Government of Kiribati elites are required to enact vulnerability in order to secure climate change adaptation financing, I demonstrate that such encounters are performative. This research contributes to theories of performativity in showing that the matrix conditioning and compelling such performative enactments of vulnerability is socionatural, consisting of a collective of climate change impacts, adaptation-finance technocrats, and many others. Thus, I demonstrate that vulnerability is not a latent condition, but, rather, an emergent effect of an assemblage of facts, expert actors, and objects.
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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 | 0.002 | 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 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".