The Logic of Resilience as Neoliberal Governmentality Informing Hurricane Katrina and Hurricane Harvey
Bibliographic record
Abstract
Despite the ascendancy of the concept of resilience in political sociology, its criticism has also expanded. In both theory and practice, this paper seeks to unpack and critically explore how resilience as embedded neoliberal governmentality permeates U.S. research in issues relating to natural environmental disasters. By highlighting the neoliberal (resilient) politics of recovery situated in two environmental disasters – Hurricane Katrina and Hurricane Harvey – this paper highlights that both pre-disaster and post-disaster recovery realities contrast starkly with the “high-minded” claims of resilience being a form of “emancipatory” resistance. Rather than being identified as natural disasters, both hurricanes are identified as voluntary failures revealing how resilience discourse was used to masquerade opportunity, subjugation, exploitation, and capital accumulation by privatepublic/state-nonstate actors. Both hurricane responses highlight that resilience embedded with a laissez-faire logic privileged types of solutions that directly hindered affected communities “bouncing back”. The third and final sections analyze an alternative conceptualization of resilience pioneered in Cuba which the United Nations International Strategy for Disaster Reduction (UNISDR) and the United Nations Development Program (UNDP) encouraged risk-reduction experts to emulate as a way forward in responding to natural environmental disasters.
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.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.055 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".