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Record W3017263846 · doi:10.1002/jid.3479

Experiencing the Everyday of Waste Pickers: A Sustainable Livelihoods and Health Assessment in Dhaka City, Bangladesh

2020· article· en· W3017263846 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of International Development · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Victoria
FundersCentre for Asia-Pacific Initiatives
KeywordsLivelihoodPovertyBusinessWork (physics)NeglectSustainable developmentUrbanizationEnvironmental planningHousehold wasteSocioeconomicsEconomic growthGeographyEngineeringEconomicsWaste managementPolitical scienceAgricultureMedicine

Abstract

fetched live from OpenAlex

Abstract Waste pickers make a livelihood by collecting recyclable waste contributing to urban development and poverty reduction. Most often, they are socially excluded and exposed to different vulnerabilities (e.g. occupational health risks and accidents). This study adopts the sustainable livelihoods framework to assess multifaceted aspects of everyday life and work experiences of waste pickers in Dhaka, Bangladesh. The framework takes an integrated and transdisciplinary approach to livelihood assets and vulnerabilities. Our findings reveal a situation of extreme poverty and neglect of waste pickers, while they are making the city more sustainable. Specific policies, strategies and actions are required to reduce risks and improve the working conditions of waste pickers. © 2020 John Wiley & Sons, Ltd.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.513

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 communication0.0000.000
Open science0.0000.001
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 head0.028
GPT teacher head0.295
Teacher spread0.267 · 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