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Record W2141978053 · doi:10.1142/s1084946713500040

EVALUATING THE GENDER VARIATIONS IN INFORMAL SECTOR ENTREPRENEURSHIP: SOME LESSONS FROM BRAZIL

2013· article· en· W2141978053 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 · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsHumber Polytechnic
Fundersnot available
KeywordsInformal sectorEntrepreneurshipRealmFemale entrepreneursEconomic growthBusinessDeveloping countryWomen entrepreneursLabour economicsEconomicsPolitical scienceFinance

Abstract

fetched live from OpenAlex

The aim of this paper is to evaluate critically the gender variations in informal sector entrepreneurship. Until now, a widely-held belief has been that entrepreneurs operating in the informal sector in developing nations are lowly paid, poorly educated, marginalized populations doing so out of necessity as a survival strategy in the absence of alternatives. Reporting an extensive 2003 survey conducted in urban Brazil of informal sector entrepreneurs operating micro-enterprises with five or less employees, the finding is that although less than half of these entrepreneurs are driven out of necessity into entrepreneurial endeavor in the informal economy, women are more commonly necessity-driven entrepreneurs and receive lower incomes from their entrepreneurial endeavor than men despite being better educated. The outcome is a call to recognize how the gender disparities in the wider labor market are mirrored and reinforced by the participation of men and women in the realm of informal sector entrepreneurship.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.123
GPT teacher head0.303
Teacher spread0.180 · 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