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Record W2404722608 · doi:10.12735/jfe.v4n3p01

Cost-Benefit Analysis of Disaster Mitigation Infrastructure: The Case of Seawalls in Otsuchi, Japan

2016· article· en· W2404722608 on OpenAlex
Kimberly Burnett, Christopher A. Wada, Aiko Endo, Makoto Taniguchi

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Finance & Economics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSeawallDamagesCorporate governanceBusinessValue (mathematics)Cost–benefit analysisEnvironmental planningEnvironmental resource managementRisk analysis (engineering)EconomicsFinanceEngineeringEnvironmental scienceComputer scienceEcologyPolitical science

Abstract

fetched live from OpenAlex

Disaster management problems often pose the same types of challenges that environmental governance problems do; they involve decision-makers at various levels and can transcend political boundaries. We conduct a benefit-cost analysis of a disaster adaptation strategy in Otsuchi, which was undertaken shortly after the 2011 Tohoku earthquake and tsunami devastated the region. Results indicate that present value net benefits from the planned seawall are positive, even if expected damages are low, provided that the wall is capable of reducing damage by at least 50%. A hybrid method of governance may, however, be effective at increasing the benefit-cost ratio.

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)0.000
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 score0.357
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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