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Record W2964506463 · doi:10.2458/v26i1.22988

Centering the Korle Lagoon: exploring blue political ecologies of E-Waste in Ghana

2019· article· en· W2964506463 on OpenAlex
Grace Akese, Peter Little

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

VenueJournal of Political Ecology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPolitical ecologyPoliticsContext (archaeology)SituatedSociologyEcologyPolitical scienceGeographyLawArchaeology

Abstract

fetched live from OpenAlex

Among emerging studies of the global political economy and ecology of electronic waste (or e-waste), few directly explore the already complex waste trades and materialities in relation to the general political ecology of water, flood control, dredging, and neoliberal ecological restoration. Even fewer focus on how this political-ecological challenge is unfolding in a West African context where ocean-based e-waste trades have played a dominant role. This article engages this particular domain of blue economic critique by focusing on Ghana in general and what we shall call "blue political ecologies of e-waste" in particular. The article focuses on e-waste politics unfolding in and around the Korle Lagoon in Accra, Ghana. The Korle Lagoon is an urban marine space of intensive land use, toxic waste disposal, social life, and urban ecological restoration. Amidst heavy contamination, there are attempts to rehabilitate the lagoon through the Korle Lagoon Ecological Restoration Project, an ecological science and restoration project focused on the Lagoon and its river system in the metropolitan area of Accra. It showcases the neoliberal complexities of ecological restoration. Importantly, situated in a multi-use marine environment, the project also highlights, we argue, a political ecological moment that is both about things 'blue', like water quality concerns, but also about other things non-blue such as contestation over land and housing, 'green' international NGO intervention on e-waste risk mitigation, and desires for new urban ecologies. Drawing on ethnographic research conducted between 2015 and 2018, this article contributes to blue political-ecological research and critique in Africa by asking: how do e-waste politics leak into discussions of the blue economy along the Korle Lagoon in Ghana? What are the promises and prospects of a blue political ecology of e-waste in general, and in Africa in particular?

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 score0.350
Threshold uncertainty score0.548

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 head0.028
GPT teacher head0.265
Teacher spread0.237 · 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