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Record W2182469971 · doi:10.5539/jsd.v8n9p240

The Achimota Transport Terminal in Accra: A Model Urban Regeneration Project in Ghana?

2015· article· en· W2182469971 on OpenAlexvenueno aff
Lewis Abedi Asante, Alexander Sasu, Jonathan Zinzi Ayitey, Naana Amakie Boakye-Agyeman

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessTaxpayerTerminal (telecommunication)SanitationNonprobability samplingGovernment (linguistics)Operations managementFinanceMarketingEconomicsComputer scienceEngineeringPopulationSociology

Abstract

fetched live from OpenAlex

<p>Over the years, government has spent millions of taxpayer’s monies to undertake urban regeneration projects (URPs) with the aim of combating the challenges of urban decay in Ghana. Several studies have argued that a number of these URPs have been left to deteriorate because there was no proper plan to maintain them. Amidst these challenges, the Achimota Transport Terminal (ATT) has been tagged as a ‘model URP in Ghana’. This paper finds out the reasons for the tag put on ATT. We adopted purposive, convenience and stratified sampling techniques to select the respondents for this study. We found two reasons for the tag on ATT – one being that the managers of ATT strictly adhere to routine and preventive maintenance practices. However, corrective maintenance was deferred. The other reason is that the terminal meets the physical (adequate parking space, availability of waiting sheds), social (creation of employment, reduction in theft cases and available cars to all destinations in Accra and beyond) and environmental (improved sanitation) dimensions of urban regeneration. Nevertheless, same cannot be said about the economic dimension (low daily sales, high maintenance cost). About 90 percent of the drivers complained vehemently of low daily sales at the terminal. We believe that delaying corrective maintenance when needed may not only mean additional cost when repairs are finally done but has the likelihood of plunging the terminal into a poor state within a short period. Additionally, since the terminal in question is serving as a model for future terminals, planning and designing of such future terminals should aim at meeting all the dimensions of urban regeneration to enhance its usage and sustainability.</p>

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.048
GPT teacher head0.295
Teacher spread0.248 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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