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Record W2081179575 · doi:10.5539/jsd.v3n4p58

Representing Interventions from the Base of the Pyramid

2010· article· en· W2081179575 on OpenAlexvenueno aff
Santosh Jagtap, Prabhu Kandachar

Bibliographic record

VenueJournal of Sustainable Development · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
Fundersnot available
KeywordsPyramid (geometry)Psychological interventionCausality (physics)Computer scienceBase (topology)Work (physics)State (computer science)BusinessRisk analysis (engineering)Operations researchEngineeringPsychologyMathematics

Abstract

fetched live from OpenAlex

The base of the world economic pyramid, generally called the base of the pyramid (BoP), consists of four billion people with average per day income of four dollars. While some authors suggest a systems approach to design and develop products and services (i.e. interventions) for BoP markets, a little work has been carried out in this area. Furthermore, a framework to represent interventions in the BoP (i.e. socio-technical systems) and the resulting changes of state is not available. The reviewed studies on technical systems include models that represent inputs and the resulting changes of state in such systems; however, these studies have not been used to represent interventions in socio-technical systems. By modifying a causality model of technical systems, this study develops a framework called the IASTS model to represent interventions in a socio-technical system. It then explains the IASTS model by analyzing two case studies drawn from the BoP.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0190.001

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 head0.018
GPT teacher head0.234
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations12
Published2010
Admission routes1
Has abstractyes

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