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Record W3210366094 · doi:10.4236/gep.2021.910005

The Socio-Economic Impacts of Aged-Dam Removal: A Review

2021· review· en· W3210366094 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.

Bibliographic record

VenueJournal of Geoscience and Environment Protection · 2021
Typereview
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsMcMaster UniversityUnited Nations University Institute for Water, Environment, and HealthUniversity of Ottawa
FundersGlobal Affairs Canada
KeywordsRecreationEconomic impact analysisEnvironmental planningValue (mathematics)Cultural heritageBusinessDam removalNatural resource economicsEnvironmental resource managementGeographyEnvironmental scienceCivil engineeringEngineeringPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Water storage dams worldwide are ageing, and many will reach the end of their designed lifespan by the middle of the 21st century. Some of these dams will likely need to be removed. While dam construction impacts have been widely discussed, dam removal impacts on society and the economy need to be synthesized and considered in the ageing dams’ decision-making process. This paper summarizes dam removal impacts on the local economy and industry, culture, history and heritage, property value, recreation, aesthetics, and disaster avoidance from identified studies worldwide. It demonstrates that these impacts may vary depending on geography and between developed and developing countries. It concludes that dam removal should consider the cost, environmental, and the socio-economic impacts while including all stakeholders who could be positively and negatively impacted by dam removal.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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