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Record W2036046525 · doi:10.1117/12.800718

Why the developing world is the perfect market place for solid state lighting

2008· article· en· W2036046525 on OpenAlexaff
Christoph Schultz, Inna Platonova, Ganesh Doluweera, Dave Irvine-Halliday

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPovertyDeveloping countryBusinessBottom of the pyramidEnergy povertyQuality (philosophy)Pyramid (geometry)State (computer science)Computer scienceTelecommunicationsEconomicsMarketingEconomic growth

Abstract

fetched live from OpenAlex

Much has been written about the daily challenge for survival faced by countless millions of developing world families and the overdeveloped world has offered a number of solutions by which those at the base of the economic pyramid (BOP) can help themselves. Light Up The World (LUTW), the global leader in bringing Renewable Energy (RE) based Solid State Lighting (SSL) to the developing world, offers yet another solution, and one that comes with a very high probability of success. In this paper we discuss: the critical role played by micro credit (banking for the poor); a typical example of a developing world community and their lighting needs and expenditures; how SSL can contribute positively to all eight of the Millennium Development Goals; the micro and macroeconomics of SSL at the BOP, its numerous societal benefits and its potential perverse outcomes; and thought there will always be a role for the donation based model, it is only through the market model that safe, healthy and affordable SSL will reach the majority of the BOP, such are the staggering numbers involved. LUTW's fundamental goal, through the facilitation of RE based SSL, is to improve the quality of life of those, who through no fault of their own, find themselves trapped in a cycle of poverty.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.779

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 communication0.0000.001
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 head0.012
GPT teacher head0.218
Teacher spread0.205 · 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 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

Citations16
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicEnergy and Environment ImpactsFrench-language works237,207