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Record W2923877367 · doi:10.1177/1078087419835968

Social and Environmental Justice in Waterfront Redevelopment: The Anacostia River, Washington, D.C.

2019· article· en· W2923877367 on OpenAlex
Nufar Avni, Raphaël Fischler

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.

Bibliographic record

VenueUrban Affairs Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsRedevelopmentEnvironmental justiceUrban regenerationEnvironmental planningEconomic JusticeSocial justiceSociologyPolitical sciencePublic administrationCriminologyGeographyLaw

Abstract

fetched live from OpenAlex

Waterfront redevelopment projects have often been criticized for prioritizing attractive skylines and glittering facades over the needs of local communities. Recently, however, they have increasingly seen goals of social and environmental justice integrated into their vision statements. This article focuses on the redevelopment of the Anacostia River in Washington, D.C. Since the early 2000s, the formerly neglected and contaminated river has been at the center of extensive regeneration efforts through the Anacostia Waterfront Initiative (AWI). We examine to what extent the AWI has helped to overcome inequities between the two disparate sides of the river. To answer this question, we build on interviews, analysis of planning documents, and site visits. Examining efforts toward both social and environmental justice, we show the convergence of the two but also the contradictions that arise between them. The findings suggest that employing a joint social and environmental justice approach to analyze waterfront redevelopments is important to reveal these tensions.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.511
Threshold uncertainty score0.893

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 science0.0000.000
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 head0.021
GPT teacher head0.285
Teacher spread0.264 · 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