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Record W4387503476 · doi:10.1142/s108494672350022x

ENABLING ECONOMIC AND SOCIAL CHANGE IN SUB-SAHARAN AFRICA: AN INFORMAL ECONOMY PERSPECTIVE

2023· article· en· W4387503476 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Developmental Entrepreneurship · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsInformal sectorPovertyLivelihoodMainstreamTransformative learningDevelopment economicsEconomicsSocial changeEconomic growthDeveloping countryDevaluationEmerging marketsSocial protectionEmbeddednessPolitical scienceSociologyGeographyAgricultureSocial science

Abstract

fetched live from OpenAlex

Research presents the informal economy as a fading phenomenon mainly confined to the peripheries of mainstream economics. However, such views overlook its transformative effect on the social and economic spheres of many regions of the developing world through employment creation. Drawing from a new dataset combining World Bank, International Monetary Fund (IMF) and Africa Index databases, this study examines the effect of country-level variables (informal economy size, economic and sustainable development) on economic and social change in twenty sub-Saharan African nations. Results reveal that informal work and informal business sustain livelihoods by providing income that helps tackle poverty, malnutrition and mortality rates. This has implications for academic research and policy making because it induces debate on the need to balance economic and social change with policy initiatives.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.086
GPT teacher head0.261
Teacher spread0.175 · 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