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An evolutionary study of production of electricity in Ghana (1900–1960s)

2020· article· en· W3035239164 on OpenAlexaff
Samuel Adu‐Gyamfi, Kwasi Amakye-Boateng, Dennis Baffour Awuah, Richard Oware, Stephen Quansah

Bibliographic record

VenueHistory of science and technology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of Saskatchewan
FundersTechnische Universiteit DelftUniversity of Pennsylvania
KeywordsElectricityElectricity generationIndigenousProduction (economics)Work (physics)BusinessNatural resource economicsEconomic growthEconomicsPower (physics)Engineering

Abstract

fetched live from OpenAlex

The literature on the history of electricity production have studied the evolution of electricity in both developed and developing countries and its impact on their economies. Some have laid foundations upon which other works are carried out. A close examination of historiography and multidisciplinary research on electricity production in Ghana shows that more efforts are required to improve the electric power landscape in Ghana. From the colonial era, the increasing demand for electricity has been the biggest challenge plaguing the energy sector. Respective governments have made significant strides in ensuring reliable and universal access to electricity throughout Ghana, yet such efforts have been accompanied by different levels of challenges. The study uses a qualitative and exploratory research approach to trace the activities that helped, in many other ways to the creation of a sustainable electric power provision to household and industry in Ghana, particularly in two of Ghana’s cities; Accra and Kumasi, within the period 1900 to the1960s. The work focused mainly on archival sources in its quest to arrive at how indigenous Ghanaians provided power for industrial activities and for household purposes. Results from the study show that local and cottage industries relied predominantly on wood, fuel, and biomass for their operations even before the introduction of the more sophisticated means of power generation. Also, the study revealed that in finding solutions to the challenges of electricity production, policymakers have focused more on current issues with little or no effort to trace the historical foundation of electricity production. This notwithstanding, the little efforts that have been made examined the history of energy production, with a limited focus on the immediate post-independence era.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0010.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

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
Published2020
Admission routes1
Has abstractyes

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