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Record W2130871854 · doi:10.1080/09603120701844258

Informal recycling and occupational health in Santo André, Brazil

2008· article· en· W2130871854 on OpenAlexafffund
Jutta Gutberlet, Angela Martins Baeder

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Victoria
FundersMichael Smith Health Research BCUniversity of Victoria
KeywordsInformal sectorHousehold wasteEnvironmental healthGovernment (linguistics)BusinessSanitationPublic healthEconomic growthSocioeconomicsMedicineEngineeringEconomicsNursing

Abstract

fetched live from OpenAlex

The collection of recyclables is a widespread activity among urban poor, particularly in countries with large socio-economic disparities. The health of recyclers is at risk because of unsafe working conditions, socio-economic exclusion, and stigmatization. Our study focuses on health problems and occupational risks of informal recyclers (in Brazil known as catadores). In 2005 we conducted an in-depth socio-economic survey of 48 informal waste collectors in Santo André, Brazil. Almost all workers reported body pain or soreness in the back, legs, shoulders, and arms. Injuries, particularly involving the hands, are frequent. Flu and bronchitis are common, and one recycler had contracted Hepatitis-B. Policy makers at all government levels need to address the pressing health issues affecting large numbers of informal recyclers in Brazil and abroad. Recyclers need to be involved in the design of waste management policies, and the public must be educated about the important environmental service these people provide.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.119
GPT teacher head0.443
Teacher spread0.324 · 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 designObservational
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

Citations152
Published2008
Admission routes2
Has abstractyes

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