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Flood hazards, environmental rewards, and the social reproduction of risk

2021· article· en· W3118430673 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeoforum · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of CanadaRyerson University
KeywordsReproductionFlood mythSocial reproductionSociologyPoliticsProduction (economics)Social capitalEnvironmental ethicsEconomicsPolitical scienceGeographySocial scienceEcologyLaw

Abstract

fetched live from OpenAlex

People pursue the environmental rewards that come with proximity to water despite associated flood risks. Governments are complicit in this exposure to flood hazards and prevailing institutional arrangements support it, begging the question of why all these actors keep making decisions that serve to reproduce risk in a society that should know better. This paper seeks to address the question by broadening the ontology of social reproduction. It draws on three disparate “imaginaries” of risk—the production of risk, risk and the social contract, and risk at the intersection of capital and rule—to make conceptual links between the production of nature, capitalist production, and social reproduction. This approach is then applied to a study of flood risk on Toronto Island, Canada. Investigating how residents there interact with environmental amenities and acute flood hazards, and how those institutionally-supported interactions are shaped by the Indigenous, environmental, and recent histories of the island, calls for a broadened social reproduction theory to hold together the general and the particular in the contingent geographies of risk. It reveals that flood risk is socially reproduced by processes working in concert to facilitate powerful groups of people in their pursuit of environmental rewards while marginalizing others, exclude some groups of people from the social contract, and situate risk as an organizing point around which lopsided bets are made within the capitalist political economy.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.003
GPT teacher head0.199
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it