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Record W7011250921

Measuring energy poverty : focusing on what matters : OPHI working paper no. 42

2011· article· en· W7011250921 on OpenAlexfundno aff

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2011
Typearticle
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsnot available
FundersInternational Atomic Energy AgencyAustralian Agency for International DevelopmentKwame Nkrumah University of Science and TechnologyUnited States Agency for International DevelopmentInternational Development Research CentreInternational Institute for Applied Systems AnalysisGovernment of CanadaDepartment for International Development
KeywordsEnergy povertyIndex (typography)Energy (signal processing)Composite indexMeasure (data warehouse)PovertyInequalityEnergy intensity
DOInot available

Abstract

fetched live from OpenAlex

<p>The provision of modern energy services is recognised as a critical foundation for sustainable\ndevelopment, and is central to the everyday lives of people. Effective policies to dramatically expand\nmodern energy access need to be grounded in a robust information-base. Metrics that can be used for\ncomparative purposes and to track progress towards targets therefore represent an essential support tool.\nThis paper reviews the relevant literature, and discusses the adequacy and applicability of existing\ninstruments to measure energy poverty. Drawing on those insights, it proposes a new composite index\nto measure energy poverty. Both the associated methodology and initial results for several African\ncountries are discussed. Whereas most existing indicators and composite indices focus on assessing the\naccess to energy, or the degree of development related to energy, our new index – the Multidimensional\nEnergy Poverty Index (MEPI) – focuses on the deprivation of access to modern energy services. It\ncaptures both the incidence and intensity of energy poverty, and provides a new tool to support policymaking.</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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.001
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 head0.048
GPT teacher head0.218
Teacher spread0.170 · 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.

Study designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

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