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Record W4387983210 · doi:10.4314/gjg.v15i2.2

Towards an Integrated Approach to Solid Waste Management in Ghanaian Cities

2023· article· en· W4387983210 on OpenAlexaff
Rosina Sheburah Essien, Moses Adjei, Victor Owusu

Bibliographic record

VenueGhana Journal of Geography · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsMemorial University of Newfoundland
FundersUniversiteit Stellenbosch
KeywordsContext (archaeology)General partnershipBusinessCitizen journalismConsumption (sociology)PoliticsEnvironmental planningEconomic growthRegional sciencePolitical scienceGeographyEconomicsSociologyFinance

Abstract

fetched live from OpenAlex

Solid Waste Management (SWM) in cities has become a theme of utmost importance in urban geographycompared to studies in rural areas which have smaller population sizes and limited consumption optionsthat are relatively more manageable. Existing studies reveal that integration of formal and informal SWMactors is the needed mechanism to overcome SWM challenges. Integration is also at the heart of the 2012Ghana National Urban Policy, yet urban spaces are zoned under public-private partnership (PPP)arrangement with private formal SWM actors. How to integrate the burgeoning numbers of privateinformal SWM service providers still remains unaddressed owing to a host of disparate institutional,political, and socio-economic factors. Using field-based data collected in three open-air markets in Accra,this paper examines the integration pathways used to include informal SWM actors in the context of PPPand thence argues for the need to rethink current SWM approaches in a participatory manner since mostGhanaian cities are facing limited financial and infrastructural resources, growing inequalities andincreasing informality regarding urban metabolism flow.

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.

How this classification was reachedexpand

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.295
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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