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Informal Work in Latin America: Competing Perspectives and Recent Debates

2008· article· en· W2110481599 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeography Compass · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLatin AmericansWork (physics)LivelihoodInformal sectorNeoliberalism (international relations)Political scienceQuarter (Canadian coin)Development economicsEconomic growthPrecarious workSociologyPolitical economyEconomicsAgricultureGeographyLaw

Abstract

fetched live from OpenAlex

Abstract During the ‘lost decade’ of the 1980s, informal work and self‐employment emerged as the most prevalent forms of work throughout Latin America. In response to the economic crisis, the majority of Latin American countries adopted a series of sweeping neoliberal reforms designed to open nations to trade and investment, promote export‐led growth, and generate employment, ultimately reducing the incidence of informal work. Despite the widespread adherence to the neoliberal model and implementation of structural adjustment reforms during the past quarter century, informal work has not diminished and in much of Latin America the odds of finding ‘decent work’ are no better today than during the economic crisis of the 1980s. In light of this seeming paradox, this article offers an overview of the recent debates and controversies surrounding informal work in Latin America. Drawing on recent research, as well as reports and policy documents from key international organizations, I pose and attempt to answer four core questions: What counts as informal work? Who works informally in Latin America? Why do men and women throughout Latin America increasingly resort to informal work? What role does informal work play as a livelihood strategy in Latin America and how has this role changed in recent years?

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 score0.041
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.212
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